Module Manual

Master

Electrical Engineering

Cohort: Winter Term 2016

Updated: 8th July 2017

Program description

Content


Core qualification

Module M0523: Business & Management

Module Responsible Prof. Matthias Meyer
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students are able to find their way around selected special areas of management within the scope of business management.
  • Students are able to explain basic theories, categories, and models in selected special areas of business management.
  • Students are able to interrelate technical and management knowledge.


Skills
  • Students are able to apply basic methods in selected areas of business management.
  • Students are able to explain and give reasons for decision proposals on practical issues in areas of business management.


Personal Competence
Social Competence
Autonomy
  • Students are capable of acquiring necessary knowledge independently by means of research and preparation of material.


Workload in Hours Depends on choice of courses
Credit points 6
Courses
Information regarding lectures and courses can be found in the corresponding module handbook published separately.

Module M0524: Nontechnical Elective Complementary Courses for Master

Module Responsible Dagmar Richter
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The Nontechnical Academic Programms (NTA)

imparts skills that, in view of the TUHH’s training profile, professional engineering studies require but are not able to cover fully. Self-reliance, self-management, collaboration and professional and personnel management competences. The department implements these training objectives in its teaching architecture, in its teaching and learning arrangements, in teaching areas and by means of teaching offerings in which students can qualify by opting for specific competences and a competence level at the Bachelor’s or Master’s level. The teaching offerings are pooled in two different catalogues for nontechnical complementary courses.

The Learning Architecture

consists of a cross-disciplinarily study offering. The centrally designed teaching offering ensures that courses in the nontechnical academic programms follow the specific profiling of TUHH degree courses.

The learning architecture demands and trains independent educational planning as regards the individual development of competences. It also provides orientation knowledge in the form of “profiles”.

The subjects that can be studied in parallel throughout the student’s entire study program - if need be, it can be studied in one to two semesters. In view of the adaptation problems that individuals commonly face in their first semesters after making the transition from school to university and in order to encourage individually planned semesters abroad, there is no obligation to study these subjects in one or two specific semesters during the course of studies.

Teaching and Learning Arrangements

provide for students, separated into B.Sc. and M.Sc., to learn with and from each other across semesters. The challenge of dealing with interdisciplinarity and a variety of stages of learning in courses are part of the learning architecture and are deliberately encouraged in specific courses.

Fields of Teaching

are based on research findings from the academic disciplines cultural studies, social studies, arts, historical studies, communication studies, migration studies and sustainability research, and from engineering didactics. In addition, from the winter semester 2014/15 students on all Bachelor’s courses will have the opportunity to learn about business management and start-ups in a goal-oriented way.

The fields of teaching are augmented by soft skills offers and a foreign language offer. Here, the focus is on encouraging goal-oriented communication skills, e.g. the skills required by outgoing engineers in international and intercultural situations.

The Competence Level

of the courses offered in this area is different as regards the basic training objective in the Bachelor’s and Master’s fields. These differences are reflected in the practical examples used, in content topics that refer to different professional application contexts, and in the higher scientific and theoretical level of abstraction in the B.Sc.

This is also reflected in the different quality of soft skills, which relate to the different team positions and different group leadership functions of Bachelor’s and Master’s graduates in their future working life.

Specialized Competence (Knowledge)

Students can

  • explain specialized areas in context of the relevant non-technical disciplines,
  • outline basic theories, categories, terminology, models, concepts or artistic techniques in the disciplines represented in the learning area,
  • different specialist disciplines relate to their own discipline and differentiate it as well as make connections, 
  • sketch the basic outlines of how scientific disciplines, paradigms, models, instruments, methods and forms of representation in the specialized sciences are subject to individual and socio-cultural interpretation and historicity,
  • Can communicate in a foreign language in a manner appropriate to the subject.
Skills

Professional Competence (Skills)

In selected sub-areas students can

  • apply basic and specific methods of the said scientific disciplines,
  • aquestion a specific technical phenomena, models, theories from the viewpoint of another, aforementioned specialist discipline,
  • to handle simple and advanced questions in aforementioned scientific disciplines in a sucsessful manner,
  • justify their decisions on forms of organization and application in practical questions in contexts that go beyond the technical relationship to the subject.



Personal Competence
Social Competence

Personal Competences (Social Skills)

Students will be able

  • to learn to collaborate in different manner,
  • to present and analyze problems in the abovementioned fields in a partner or group situation in a manner appropriate to the addressees,
  • to express themselves competently, in a culturally appropriate and gender-sensitive manner in the language of the country (as far as this study-focus would be chosen), 
  • to explain nontechnical items to auditorium with technical background knowledge.





Autonomy

Personal Competences (Self-reliance)

Students are able in selected areas

  • to reflect on their own profession and professionalism in the context of real-life fields of application
  • to organize themselves and their own learning processes      
  • to reflect and decide questions in front of a broad education background
  • to communicate a nontechnical item in a competent way in writen form or verbaly
  • to organize themselves as an entrepreneurial subject country (as far as this study-focus would be chosen)     



Workload in Hours Depends on choice of courses
Credit points 6
Courses
Information regarding lectures and courses can be found in the corresponding module handbook published separately.

Module M0676: Digital Communications

Courses
Title Typ Hrs/wk CP
Digital Communications (L0444) Lecture 2 3
Digital Communications (L0445) Recitation Section (large) 1 2
Laboratory Digital Communications (L0646) Laboratory Course 1 1
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics 1-3
  • Signals and Systems
  • Fundamentals of Communications and Random Processes
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students are able to understand, compare and design modern digital information transmission schemes. They are familiar with the properties of linear and non-linear digital modulation methods. They can describe distortions caused by transmission channels and design and evaluate detectors including channel estimation and equalization. They know the principles of single carrier transmission and multi-carrier transmission as well as the fundamentals of basic multiple access schemes.
Skills The students are able to design and analyse a digital information transmission scheme including multiple access. They are able to choose a digital modulation scheme taking into account transmission rate, required bandwidth, error probability, and further signal properties. They can design an appropriate detector including channel estimation and equalization taking into account performance and complexity properties of suboptimum solutions. They are able to set parameters of a single carrier or multi carrier transmission scheme and trade the properties of both approaches against each other.
Personal Competence
Social Competence

The students can jointly solve specific problems.

Autonomy

The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems: Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Course L0444: Digital Communications
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle WiSe
Content
  • Digital modulation methods

  • Coherent and non-coherent detection

  • Channel estimation and equalization

  • Single-Carrier- and multi carrier transmission schemes, multiple access schemes (TDMA, FDMA, CDMA, OFDM)

Literature

K. Kammeyer: Nachrichtenübertragung, Teubner

P.A. Höher: Grundlagen der digitalen Informationsübertragung, Teubner.

J.G. Proakis, M. Salehi: Digital Communications. McGraw-Hill.

S. Haykin: Communication Systems. Wiley

R.G. Gallager: Principles of Digital Communication. Cambridge

A. Goldsmith: Wireless Communication. Cambridge.

D. Tse, P. Viswanath: Fundamentals of Wireless Communication. Cambridge.

Course L0445: Digital Communications
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0646: Laboratory Digital Communications
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle WiSe
Content

- DSL transmission

- Random processes

- Digital data transmission

Literature

K. Kammeyer: Nachrichtenübertragung, Teubner

P.A. Höher: Grundlagen der digitalen Informationsübertragung, Teubner.

J.G. Proakis, M. Salehi: Digital Communications. McGraw-Hill.

S. Haykin: Communication Systems. Wiley

R.G. Gallager: Principles of Digital Communication. Cambridge

A. Goldsmith: Wireless Communication. Cambridge.

D. Tse, P. Viswanath: Fundamentals of Wireless Communication. Cambridge.

Module M0746: Microsystem Engineering

Courses
Title Typ Hrs/wk CP
Microsystem Engineering (L0680) Lecture 2 4
Microsystem Engineering (L0682) Problem-based Learning 1 1
Microsystem Engineering (L0681) Recitation Section (small) 1 1
Module Responsible Prof. Manfred Kasper
Admission Requirements
Recommended Previous Knowledge

Electrical Engineering Fundamentals

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students know about the most important technologies and materials of MEMS as well as their applications in sensors and actuators.

Skills

Students are able to analyze and describe the functional behaviour of MEMS components and to evaluate the potential of microsystems.

Personal Competence
Social Competence

Students are able to solve specific problems alone or in a group and to present the results accordingly.

Autonomy

Students are able to acquire particular knowledge using specialized literature and to integrate and associate this knowledge with other fields.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale zweistündig
Assignment for the Following Curricula Electrical Engineering: Core qualification: Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0680: Microsystem Engineering
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Manfred Kasper
Language EN
Cycle WiSe
Content

Object and goal of MEMS

Scaling Rules

Lithography

Film deposition

Structuring and etching

Energy conversion and force generation

Electromagnetic Actuators

Reluctance motors

Piezoelectric actuators, bi-metal-actuator

Transducer principles

Signal detection and signal processing

Mechanical and physical sensors

Acceleration sensor, pressure sensor

Sensor arrays

System integration

Yield, test and reliability

Literature

M. Kasper: Mikrosystementwurf, Springer (2000)

M. Madou: Fundamentals of Microfabrication, CRC Press (1997)

Course L0682: Microsystem Engineering
Typ Problem-based Learning
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Manfred Kasper
Language EN
Cycle WiSe
Content

Examples of MEMS components

Layout consideration

Electric, thermal and mechanical behaviour

Design aspects

Literature

Wird in der Veranstaltung bekannt gegeben

Course L0681: Microsystem Engineering
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Manfred Kasper
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0710: Microwave Engineering

Courses
Title Typ Hrs/wk CP
Microwave Engineering (L0573) Lecture 2 3
Microwave Engineering (L0574) Recitation Section (large) 2 2
Microwave Engineering (L0575) Laboratory Course 1 1
Module Responsible Prof. Arne Jacob
Admission Requirements
Recommended Previous Knowledge

Fundamentals of communication engineering, semiconductor devices and circuits. Basics of Wave propagation from transmission line theory and theoretical electrical engineering.

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the propagation of electromagnetic waves and related phenomena. They can describe transmission systems and components. They can name different types of antennas and describe the main characteristics of antennas. They can explain noise in linear circuits, compare different circuits using characteristic numbers and select the best one for specific scenarios.


Skills

Students are able to calculate the propagation of electromagnetic waves. They can analyze complete transmission systems und configure simple receiver circuits. They can calculate the characteristic of simple antennas and arrays based on the geometry. They can calculate the noise of receivers and the signal-to-noise-ratio of transmission systems. They can apply their theoretical knowledge to the practical courses.


Personal Competence
Social Competence

Students work together in small groups during the practical courses. Together they document, evaluate and discuss their results.


Autonomy

Students are able to relate the knowledge gained in the course to contents of previous lectures. With given instructions they can extract data needed to solve specific problems from external sources. They are able to apply their knowledge to the laboratory courses using the given instructions.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Electrical Engineering: Core qualification: Compulsory
Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Course L0573: Microwave Engineering
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle WiSe
Content

- Antennas: Analysis - Characteristics - Realizations

- Radio Wave Propagation

- Transmitter: Power Generation with Vacuum Tubes and Transistors

- Receiver: Preamplifier - Heterodyning - Noise

- Selected System Applications


Literature

H.-G. Unger, „Elektromagnetische Theorie für die Hochfrequenztechnik, Teil I“, Hüthig, Heidelberg, 1988

H.-G. Unger, „Hochfrequenztechnik in Funk und Radar“, Teubner, Stuttgart, 1994

E. Voges, „Hochfrequenztechnik - Teil II: Leistungsröhren, Antennen und Funkübertragung, Funk- und Radartechnik“, Hüthig, Heidelberg, 1991

E. Voges, „Hochfrequenztechnik“, Hüthig, Bonn, 2004


C.A. Balanis, “Antenna Theory”, John Wiley and Sons, 1982

R. E. Collin, “Foundations for Microwave Engineering”, McGraw-Hill, 1992

D. M. Pozar, “Microwave and RF Design of Wireless Systems”, John Wiley and Sons, 2001

D. M. Pozar, “Microwave Engineerin”, John Wiley and Sons, 2005


Course L0574: Microwave Engineering
Typ Recitation Section (large)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0575: Microwave Engineering
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0846: Control Systems Theory and Design

Courses
Title Typ Hrs/wk CP
Control Systems Theory and Design (L0656) Lecture 2 4
Control Systems Theory and Design (L0657) Recitation Section (small) 2 2
Module Responsible Prof. Herbert Werner
Admission Requirements None
Recommended Previous Knowledge Introduction to Control Systems
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain how linear dynamic systems are represented as state space models; they can interpret the system response to initial states or external excitation as trajectories in state space
  • They can explain the system properties controllability and observability, and their relationship to state feedback and state estimation, respectively
  • They can explain the significance of a minimal realisation
  • They can explain observer-based state feedback and how it can be used to achieve tracking and disturbance rejection
  • They can extend all of the above to multi-input multi-output systems
  • They can explain the z-transform and its relationship with the Laplace Transform
  • They can explain state space models and transfer function models of discrete-time systems
  • They can explain the experimental identification of ARX models of dynamic systems, and how the identification problem can be solved by solving a normal equation
  • They can explain how a state space model can be constructed from a discrete-time impulse response

Skills
  • Students can transform transfer function models into state space models and vice versa
  • They can assess controllability and observability and construct minimal realisations
  • They can design LQG controllers for multivariable plants
  •  They can carry out a controller design both in continuous-time and discrete-time domain, and decide which is  appropriate for a given sampling rate
  • They can identify transfer function models and state space models of dynamic systems from experimental data
  • They can carry out all these tasks using standard software tools (Matlab Control Toolbox, System Identification Toolbox, Simulink)

Personal Competence
Social Competence

Students can work in small groups on specific problems to arrive at joint solutions. 

Autonomy

Students can obtain information from provided sources (lecture notes, software documentation, experiment guides) and use it when solving given problems.

They can assess their knowledge in weekly on-line tests and thereby control their learning progress.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 120 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Compulsory
Energy Systems: Core qualification: Elective Compulsory
Aircraft Systems Engineering: Specialisation Aircraft Systems: Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Core qualification: Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Product Development, Materials and Production: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Compulsory
Course L0656: Control Systems Theory and Design
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle WiSe
Content

State space methods (single-input single-output)

• State space models and transfer functions, state feedback 
• Coordinate basis, similarity transformations 
• Solutions of state equations, matrix exponentials, Caley-Hamilton Theorem
• Controllability and pole placement 
• State estimation, observability, Kalman decomposition 
• Observer-based state feedback control, reference tracking 
• Transmission zeros
• Optimal pole placement, symmetric root locus 
Multi-input multi-output systems
• Transfer function matrices, state space models of multivariable systems, Gilbert realization 
• Poles and zeros of multivariable systems, minimal realization 
• Closed-loop stability
• Pole placement for multivariable systems, LQR design, Kalman filter 

Digital Control
• Discrete-time systems: difference equations and z-transform 
• Discrete-time state space models, sampled data systems, poles and zeros 
• Frequency response of sampled data systems, choice of sampling rate 

System identification and model order reduction 
• Least squares estimation, ARX models, persistent excitation 
• Identification of state space models, subspace identification 
• Balanced realization and model order reduction 

Case study
• Modelling and multivariable control of a process evaporator using Matlab and Simulink 
Software tools
• Matlab/Simulink

Literature
  • Werner, H., Lecture Notes „Control Systems Theory and Design“
  • T. Kailath "Linear Systems", Prentice Hall, 1980
  • K.J. Astrom, B. Wittenmark "Computer Controlled Systems" Prentice Hall, 1997
  • L. Ljung "System Identification - Theory for the User", Prentice Hall, 1999
Course L0657: Control Systems Theory and Design
Typ Recitation Section (small)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0913: CMOS Nanoelectronics with Practice

Courses
Title Typ Hrs/wk CP
CMOS Nanoelectronics (L0764) Lecture 2 3
CMOS Nanoelectronics (L1063) Laboratory Course 2 2
CMOS Nanoelectronics (L1059) Recitation Section (small) 1 1
Module Responsible Prof. Wolfgang Krautschneider
Admission Requirements None
Recommended Previous Knowledge Fundamentals of MOS devices and electronic circuits
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the functionality of very small  MOS transistors and explain the problems occurring due to scaling-down the minimum feature size.
  • Students are able to explain the basic steps of processing of very small MOS devices.
  • Students can exemplify the functionality of volatile and non-volatile memories und give their specifications.
  • Students can describe the limitations of advanced MOS technologies.
  • Students can explain measurement methods for MOS quality control.


Skills
  • Students can quantify the current-voltage-behavior of very small MOS transistors and list possible applications.
  • Students can describe larger electronic systems by their functional blocks.
  • Students can name the existing options for the specific applications and select the most appropriate ones.


Personal Competence
Social Competence
  • Students can team up with one or several partners who may have different professional backgrounds
  • Students are able to work by their own or in small groups for solving problems and answer scientific questions.


Autonomy
  • Students are able to assess their knowledge in a realistic manner.
  • The students are able to draw scenarios for estimation of the impact of advanced mobile electronics on the future lifestyle of the society.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Core qualification: Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0764: CMOS Nanoelectronics
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Wolfgang Krautschneider
Language EN
Cycle WiSe
Content
  • Ideal and non-ideal MOS devices
  • Threshold voltage, Parasitic charges, Work function difference
  • I-V behavior
  • Scaling-down rules
  • Details of very small MOS transistors
  • Basic CMOS process flow
  • Memory Technology, SRAM, DRAM, embedded DRAM
  • Gain memory cells
  • Non-volatile memories, Flash memory circuits
  • Methods for Quality Control, C(V)-technique, Charge pumping, Uniform injection
  • Systems with extremely small CMOS transistors
Literature
  • S. Deleonibus, Electronic Device Architectures for the Nano-CMOS Era, Pan Stanford Publishing, 2009.
  • Y. Taur and T.H. Ning, Fundamentals of Modern VLSI Devices, Cambridge University Press, 2nd edition.
  • R.F. Pierret, Advanced Semiconductor Fundamentals, Prentice Hall, 2003.
  • F. Schwierz, H. Wong, J. J. Liou, Nanometer CMOS, Pan Stanford Publishing, 2010.
  • H.-G. Wagemann und T. Schönauer, Silizium-Planartechnologie, Grundprozesse, Physik und Bauelemente
    Teubner-Verlag, 2003, ISBN 3519004674


Course L1063: CMOS Nanoelectronics
Typ Laboratory Course
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Wolfgang Krautschneider
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L1059: CMOS Nanoelectronics
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Wolfgang Krautschneider
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0798: Technical Complementary Course I for ETMS (according to Subject Specific Regulations)

Courses
Title Typ Hrs/wk CP
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge See selected module according to FSPO


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

see selected module according to FSPO


Skills

see selected module according to FSPO


Personal Competence
Social Competence

see selected module according to FSPO


Autonomy

see selected module according to FSPO


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination according to Subject Specific Regulations
Examination duration and scale according to module description
Assignment for the Following Curricula Electrical Engineering: Core qualification: Compulsory

Module M0799: Technical Complementary Course II for ETMS (according to Subject Specific Regulations)

Courses
Title Typ Hrs/wk CP
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge

See selected module according to FSPO

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

see selected module according to FSPO

Skills

see selected module according to FSPO

Personal Competence
Social Competence

see selected module according to FSPO

Autonomy

see selected module according to FSPO

Workload in Hours Independent Study Time 180, Study Time in Lecture 0
Credit points 6
Examination according to Subject Specific Regulations
Examination duration and scale according to module description
Assignment for the Following Curricula Electrical Engineering: Core qualification: Compulsory

Specialization Microwave Engineering, Optics, and Electromagnetic Compatibility

Module M0548: Bioelectromagnetics: Principles and Applications

Courses
Title Typ Hrs/wk CP
Bioelectromagnetics: Principles and Applications (L0371) Lecture 3 5
Bioelectromagnetics: Principles and Applications (L0373) Recitation Section (small) 2 1
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge

Basic principles of physics


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the basic principles, relationships, and methods of bioelectromagnetics, i.e. the quantification and application of electromagnetic fields in biological tissue. They can define and exemplify the most important physical phenomena and order them corresponding to wavelength and frequency of the fields. They can give an overview over measurement and numerical techniques for characterization of electromagnetic fields in practical applications . They can give examples for therapeutic and diagnostic utilization of electromagnetic fields in medical technology.


Skills

Students know how to apply various methods to characterize the behavior of electromagnetic fields in biological tissue.  In order to do this they can relate to and make use of the elementary solutions of Maxwell’s Equations. They are able to assess the most important effects that these models predict for biological tissue, they can order the effects corresponding to wavelength and frequency, respectively, and they can analyze them in a quantitative way. They are able to develop validation strategies for their predictions. They are able to evaluate the effects of electromagnetic fields for therapeutic and diagnostic applications and make an appropriate choice.


Personal Competence
Social Competence

Students are able to work together on subject related tasks in small groups. They are able to present their results effectively in English (e.g. during small group exercises).


Autonomy

Students are capable to gather information from subject related, professional publications and relate that information to the context of the lecture. They are able to make a connection between their knowledge obtained in this lecture with the content of other lectures (e.g. theory of electromagnetic fields, fundamentals of electrical engineering / physics). They can communicate problems and effects in the field of bioelectromagnetics in English.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Oral exam
Examination duration and scale 30-60 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Course L0371: Bioelectromagnetics: Principles and Applications
Typ Lecture
Hrs/wk 3
CP 5
Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle SoSe
Content

- Fundamental properties of electromagnetic fields (phenomena)

- Mathematical description of electromagnetic fields (Maxwell’s Equations)

- Electromagnetic properties of biological tissue

- Principles of energy absorption in biological tissue, dosimetry

- Numerical methods for the computation of electromagnetic fields (especially FDTD)

- Measurement techniques for characterization of electromagnetic fields

- Behavior of electromagnetic fields of low frequency in biological tissue

- Behavior of electromagnetic fields of medium frequency in biological tissue

- Behavior of electromagnetic fields of high frequency in biological tissue

- Behavior of electromagnetic fields of very high frequency in biological tissue

- Diagnostic applications of electromagnetic fields in medical technology

- Therapeutic applications of electromagnetic fields in medical technology

- The human body as a generator of electromagnetic fields


Literature

- C. Furse, D. Christensen, C. Durney, "Basic Introduction to Bioelectromagnetics", CRC (2009)

- A. Vorst, A. Rosen, Y. Kotsuka, "RF/Microwave Interaction with Biological Tissues", Wiley (2006)

- S. Grimnes, O. Martinsen, "Bioelectricity and Bioimpedance Basics", Academic Press (2008)

- F. Barnes, B. Greenebaum, "Bioengineering and Biophysical Aspects of Electromagnetic Fields", CRC (2006)


Course L0373: Bioelectromagnetics: Principles and Applications
Typ Recitation Section (small)
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle SoSe
Content

- Fundamental properties of electromagnetic fields (phenomena)

- Mathematical description of electromagnetic fields (Maxwell’s Equations)

- Electromagnetic properties of biological tissue

- Principles of energy absorption in biological tissue, dosimetry

- Numerical methods for the computation of electromagnetic fields (especially FDTD)

- Measurement techniques for characterization of electromagnetic fields

- Behavior of electromagnetic fields of low frequency in biological tissue

- Behavior of electromagnetic fields of medium frequency in biological tissue

- Behavior of electromagnetic fields of high frequency in biological tissue

- Behavior of electromagnetic fields of very high frequency in biological tissue

- Diagnostic applications of electromagnetic fields in medical technology

- Therapeutic applications of electromagnetic fields in medical technology

- The human body as a generator of electromagnetic fields


Literature

- C. Furse, D. Christensen, C. Durney, "Basic Introduction to Bioelectromagnetics", CRC (2009)

- A. Vorst, A. Rosen, Y. Kotsuka, "RF/Microwave Interaction with Biological Tissues", Wiley (2006)

- S. Grimnes, O. Martinsen, "Bioelectricity and Bioimpedance Basics", Academic Press (2008)

- F. Barnes, B. Greenebaum, "Bioengineering and Biophysical Aspects of Electromagnetic Fields", CRC (2006)


Module M0643: Optoelectronics I - Wave Optics

Courses
Title Typ Hrs/wk CP
Optoelectronics I: Wave Optics (L0359) Lecture 2 3
Optoelectronics I: Wave Optics (Problem Solving Course) (L0361) Recitation Section (small) 1 1
Module Responsible Prof. Manfred Eich
Admission Requirements

Keine

Recommended Previous Knowledge

Basics in electrodynamics, calculus


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the fundamental mathematical and physical relations of freely propagating optical waves.
They can give an overview on wave optical phenomena such as diffraction, reflection and refraction, etc. 
Students can describe waveoptics based components such as electrooptical modulators in an application oriented way.



Skills

Students can generate models and derive mathematical descriptions in relation to free optical wave propagation.
They can derive approximative solutions and judge factors influential on the components' performance.


Personal Competence
Social Competence

Students can jointly solve subject related problems in groups. They can present their results effectively within the framework of the problem solving course.


Autonomy

Students are capable to extract relevant information from the provided references and to relate this information to the content of the lecture. They can reflect their acquired level of expertise with the help of lecture accompanying measures such as exam typical exam questions. Students are able to connect their knowledge with that acquired from other lectures.


Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Written exam
Examination duration and scale 40 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Materials Science: Specialisation Nano and Hybrid Materials: Elective Compulsory
Microelectronics and Microsystems: Specialisation Microelectronics Complements: Elective Compulsory
Course L0359: Optoelectronics I: Wave Optics
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Manfred Eich
Language EN
Cycle SoSe
Content
  • Introduction to optics
  • Electromagnetic theory of light
  • Interference
  • Coherence
  • Diffraction
  • Fourier optics
  • Polarisation and Crystal optics
  • Matrix formalism
  • Reflection and transmission
  • Complex refractive index
  • Dispersion
  • Modulation and switching of light
Literature

Bahaa E. A. Saleh, Malvin Carl Teich, Fundamentals of Photonics, Wiley 2007 
Hecht, E., Optics, Benjamin Cummings, 2001
Goodman, J.W. Statistical Optics, Wiley, 2000
Lauterborn, W., Kurz, T., Coherent Optics: Fundamentals and Applications, Springer, 2002

Course L0361: Optoelectronics I: Wave Optics (Problem Solving Course)
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Manfred Eich
Language EN
Cycle SoSe
Content see lecture Optoelectronics 1 - Wave Optics
Literature

see lecture Optoelectronics 1 - Wave Optics

Module M1016: Optical Communication

Courses
Title Typ Hrs/wk CP
Optical Communication (L0477) Lecture 2 3
Optical Communication (L0480) Recitation Section (large) 1 1
Module Responsible Dr. Hagen Renner
Admission Requirements
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Oral exam
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Course L0477: Optical Communication
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Hagen Renner
Language EN
Cycle SoSe
Content

Optical Communications 

  • Optical waveguide fundamentals 
    • total internal reflection at plane dielectric interfaces
    • slab waveguides
    • rays in step-index and graded-index “multi-mode” fibers
    • modes in optical fibers
    • single-mode fibers
    • fabrication of fibers
  • Properties of silica optical fiber relevant in communications
    • attenuation by scattering and absorption
    • dispersion and pulse broadening
    • polarization mode dispersion
  • Passive fiber optical components
    • excitation of fibers, splice/connector loss
    • fiber optical directional couplers
    • isolators, circulators, phased arrays, grating components
  • Photodiode and LED fundamentals
    • pin-photodiodes: responsivity, response time, equivalent circuit
    • avalanche photodiodes
    • light emitting diodes: spectra, output power, modulation
  • Noise in photodetectors 
    • power spectral density of a train of randomly occuring events
    • shot noise and thermal noise
    • photodetector equivalent circuits with noise sources
    • basic receiver considerations
  • Laserdiodes
    • basic laser physics
    • Fabry-Perot laser diodes
    • rate equations and LD characteristics
    • special laser diodes
  • Optical fiber amplifiers
    • Erbium in silica fibers: energy levels, transitions, cross sections, amplification                                            
    • noise in optical amplifiers: spontaneous emission, ASE, noise figure, periodic amplification
    • modelling of optical amplifiers
    • examples and applications
  • Nonlinearities in optical fibers
    • basic nonlinear effects
    • solitons for high bit rate transmission: dispersion vs. self phase modulation
  • Optical fiber systems
Literature

[1]        G.P. Agrawal, "Fiber-optic communication systems", Wiley-Interscience, 2002

[2]        J. Gowar: “Opical Communication Systems“, Prentice Hall 199

[3]         I.P. Kaminov and L. Koch (ed.): “Optical Fiber Telecomminications“,

            volume IIIA and IIIB, Academic Press, 1997

[4]        A. Yariv: “Optical Electronics“, Sauders College Publishing, 1997

[5]        E.G. Neumann: “Single-Mode Fibers“, Springer 1988

[6]        H.G. Unger: “Optische Nachrichtentechnik“, volume I and II, Hüthig 1992

            (in German)

[7]        J.M. Senior: “Optical Fiber communications“, Prentice Hall 2009

[8]        E. Voges and K. Petermann (ed.): “Optische Kommunikationstechnik”,

            Springer 2002 (in German)

Course L0480: Optical Communication
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Hagen Renner
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0645: Fibre and Integrated Optics

Courses
Title Typ Hrs/wk CP
Fibre and Integrated Optics (L0363) Lecture 2 3
Fibre and Integrated Optics (Problem Solving Course) (L0365) Recitation Section (small) 1 1
Module Responsible Prof. Manfred Eich
Admission Requirements None
Recommended Previous Knowledge

Basic principles of electrodynamics and optics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the fundamental mathematical and physical relations and technological basics of guided optical waves. They can describe integrated optical as well as fibre optical structures. They can give an overview on the applications of integrated optical components in optical signal processing.

Skills

Students can generate models and derive mathematical descriptions in relation to fibre optical and integrated optical wave propagation. They can derive approximative solutions and judge factors influential on the components' performance.


Personal Competence
Social Competence Students can jointly solve subject related problems in groups. They can present their results effectively within the framework of the problem solving course.
Autonomy

Students are capable to extract relevant information from the provided references and to relate this information to the content of the lecture. They can reflect their acquired level of expertise with the help of lecture accompanying measures such as exam typical exam questions. Students are able to connect their knowledge with that acquired from other lectures.

Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Written exam
Examination duration and scale 40 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Course L0363: Fibre and Integrated Optics
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Hagen Renner
Language EN
Cycle SoSe
Content
  • Theory of optical waveguides
  • Coupling to and from waveguides
  • Losses
  • Linear and nonlinear dspersion
  • Components and technical applications
Literature

Bahaa E. A. Saleh, Malvin Carl Teich, Fundamentals of Photonics, Wiley 2007
Hunsperger, R.G., Integrated Optics: Theory and Technology, Springer, 2002
Agrawal, G.P.,Fiber-Optic Communication Systems, Wiley, 2002, ISBN 0471215716
Marcuse, D., Theory of Dielectric Optical Waveguides, Academic Press,1991, ISBN 0124709516
Tamir, T. (ed), Guided-Wave Optoelectronics, Springer, 1990

Course L0365: Fibre and Integrated Optics (Problem Solving Course)
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Hagen Renner
Language EN
Cycle SoSe
Content

See lecture Fibre and Integrated Optics

Literature

See lecture Fibre and Integrated Optics

Module M0712: Microwave Semiconductor Devices and Circuits I

Courses
Title Typ Hrs/wk CP
Microwave Semiconductor Devices and Circuits I (L0580) Lecture 3 4
Microwave Semiconductor Devices and Circuits I (L0581) Recitation Section (large) 2 2
Module Responsible Prof. Arne Jacob
Admission Requirements
Recommended Previous Knowledge

Electrical Engineering IV, Microwave Engineering, Fundamentals of Semiconductor Technology


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are capable of explaining the functionality of amplifier, mixer, and oscillator in detail. They can present theories, concepts, and reasonable assumptions for description and synthesis of these devices. They are able to apply thorough knowledge of semiconductor physics of selected microwave devices to amplifier, mixer, and oscillator. They can compare different devices with respect to various parameters (such as frequency range, power und efficiency).


Skills

The students can assess occurring linear and nonlinear effects in active microwave circuits and are capable of analyzing and evaluating them. They are able to develop passive and active linear microwave circuits with the help of modern software-tools, taking application requirements into account.


Personal Competence
Social Competence

The students are able to carry out subject-specific tasks in small groups, and to adequately present solutions (e.g. in CAD-Exercises).


Autonomy

The students are able to obtain additional information from given literature sources and set the content in context with the lecture. They can link and deepen their knowledge of other courses, e.g., Electrical Engineering IV, Theoretical Engineering, Microwave Engineering, Semiconductor Devices. The students acquire the ability to communicate problems and solutions in the field of microwave semiconductor devices and circuits in English.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Oral exam
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Course L0580: Microwave Semiconductor Devices and Circuits I
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle SoSe
Content

- Amplifier: S-Parameters, stability, gain definitions; Bipolar Junction Transistor and HBT, MESFET and HEMT; Circuit applications, nonlinear distortions, low noise and power amplifier

- Mixer: Conversion matrix analysis; pn- and Schottky-diode, FET; Circuit applications, conversion gain and noise figure

- Oszillator: Oscillation start-up, steady state operation, stability; IMPATT-diode, Gunn-element, FET; oscillator stabilization

- Linear passive circuits: Planar microwave circuits, quarterwave matching circuits and discontinuities, lowpass-filter and bandpass-filter synthesis

- Design of active circuits


Literature

- E. Voges, „Hochfrequenztechnik“, Hüthig (2004)

- H.-G. Unger, W. Harth, „Hochfrequenz-Halbleiterelektronik“, S. Hirzel Verlag (1972)

- S.M. Sze, „Physics of Semiconductor Devices”, John Wiley & Sons (1981)
- A. Jacob, „Lecture Notes Microwave Semiconductor Devices and Circuits Part I“


Course L0581: Microwave Semiconductor Devices and Circuits I
Typ Recitation Section (large)
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0769: EMC I: Couplings, Countermeasures and Test Procedures

Courses
Title Typ Hrs/wk CP
EMC I: Couplings, Countermeasures, and Test Procedures (L0743) Lecture 3 4
EMC I: Couplings, Countermeasures, and Test Procedures (L0744) Recitation Section (small) 1 1
EMC I: Couplings, Countermeasures, and Test Procedures (L0745) Laboratory Course 1 1
Module Responsible Prof. Christian Schuster
Admission Requirements

None

Recommended Previous Knowledge

Fundamentals of Electrical Engineering

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain the fundamental principles, inter-dependencies, and methods of Electromagnetic Compatibility of electric and electronic systems and to ensure Electromagnetic Compatibility of such systems. They are able to classify and explain the common interference sources and coupling mechanisms. They are capable of explaining the basic principles of shielding and filtering.  They are able of giving an overview over measurement and simulation methods for the characterization of Electromagnetic Compatibility in electrical engineering practice.

Skills

Students are able to apply a series of modeling methods for the Electromagnetic Compatibility of typical electric and electronic systems. They are able to determine the most important effects that these models are predicting in terms of Electromagnetic Compatibility. They can classify these effects and they can quantitatively analyze them. They are capable of deriving problem solving strategies from these predictions and they can adapt them to applications in electrical engineering practice. They can evaluate their problem solving strategies against each other.

Personal Competence
Social Competence

Students are able to work together on subject related tasks in small groups. They are able to present their results effectively in English, during laboratory work and exercises, e.g..

Autonomy

Students are capable to gather necessary information from the references provided and relate that information to the context of the lecture. They are able to make a connection between their knowledge obtained in this lecture with the content of other lectures (e.g. Theoretical Electrical Engineering and Communication Theory). They can communicate problems and solutions in the field of Electromagnetic Compatibility in english language.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Oral exam
Examination duration and scale 30 bis 60 Minuten
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Course L0743: EMC I: Couplings, Countermeasures, and Test Procedures
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle SoSe
Content
  • Introduction to Electromagnetic Compatibility (EMC)
  • Interference sources in time an frequency domain
  • Coupling mechanisms
  • Transmission lines and coupling to electromagnetic fields
  • Shielding
  • Filters
  • EMC test procedures
Literature
  • C.R. Paul: "Introduction to Electromagnetic Compatibility", 2nd ed., (Wiley, New Jersey, 2006).
  • A.J. Schwab und W. Kürner: "Elektromagnetische Verträglichkeit", 6. Auflage, (Springer, Berlin 2010).
  • F.M. Tesche, M.V. Ianoz, and T. Karlsson: "EMC Analysis Methods and Computational Models", (Wiley, New York, 1997).
Course L0744: EMC I: Couplings, Countermeasures, and Test Procedures
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle SoSe
Content

The exercise sessions serve to deepen the understanding of the concepts of the lecture.

Literature
  • C.R. Paul: "Introduction to Electromagnetic Compatibility", 2nd ed., (Wiley, New Jersey, 2006).
  • A.J. Schwab und W. Kürner: "Elektromagnetische Verträglichkeit", 6. Auflage, (Springer, Berlin 2010).
  • F.M. Tesche, M.V. Ianoz, and T. Karlsson: "EMC Analysis Methods and Computational Models", (Wiley, New York, 1997).
  • Scientific articles and papers
Course L0745: EMC I: Couplings, Countermeasures, and Test Procedures
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle SoSe
Content

Laboratory experiments serve to practically investigate the following EMC topics:

  • Shielding
  • Conducted EMC test procedures
  • The GTEM-cell as an environment for radiated EMC test
Literature Versuchsbeschreibungen und zugehörige Literatur werden innerhalb der Veranstaltung bereit gestellt.

Module M0784: Introduction to Antenna Theory

Courses
Title Typ Hrs/wk CP
Introduction To Antenna Theory (L0783) Lecture 2 3
Introduction To Antenna Theory (L0784) Recitation Section (large) 1 1
Introduction To Antenna Theory (L1349) Laboratory Course 1 2
Module Responsible Prof. Arne Jacob
Admission Requirements
Recommended Previous Knowledge

Electrical Engineering IV, Theoretical Electrical Engineering II, Microwave Engineering


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are able to apply the fundamental theory and approximations regarding the propagation of electromagnetic waves on transmission lines and in free space specifically with regard to antenna design problems. They are able to evaluate which method of analysis is suitable for certain antennas. They are able to derive the field solutions for different antenna types. The students are able to illustrate the functionality and radiation behavior of antennas based on physical principles. Additionally, the functionality of arrangements of several antennas (arrays) can be evaluated by the students.


Skills

The students are capable of applying different methods which are used for antenna characterization in a problem related manner. By means of the analysis of different antenna types the students are able to assess which antenna is adequate for a certain situation, e.g., with respect to the radiation pattern or the input resistance. They have the knowledge to handle advanced antenna and radiation problems in an autonomous way. In lecture-accompanying CAD exercises and laboratory experiments the students are capable of verifying the related approximations and assessing their accuracy and validity. This way, they are able to compare the theory with numerical and experimental methods.


Personal Competence
Social Competence

The students are able to work in small groups in the CAD exercises and the laboratory experiments to discuss tasks related to the subject. They are able to present and demonstrate their knowledge in a suitable manner.


Autonomy

The students are able to obtain supplementary information from the indicated literature sources and to relate it to the content of the lecture. They are capable of deepening and linking their achieved knowledge with the contents of other lectures (e.g. Microwave Engineering, Theoretical Electrical Engineering II). The students acquire the ability to choose and develop the right antenna type for a certain situation under given conditions in a self-contained way.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Course L0783: Introduction To Antenna Theory
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle SoSe
Content

- Basic principles: Near and far field, approximate solutions, Poynting Theorem

- Wire antennas: loop antenna, folded dipole, discone and conical-skirt monopole, traveling-wave antenna, long-wire antenna, helical antenna

- Horn antennas: rectangular aperture, circular aperture, corrugated horn

- Reflector antennas: Geometrical Optics, Geometrical Theory of Diffraction

- Antenna arrays: array factor, beam scanning, uniformly and non-uniformly excited linear arrays, array feeds

- CAD tools for electrical analysis and design of antennas and arrays


- Experimental antenna characterization

Literature

- H.-G. Unger, "Hochfrequenztechnik in Funk und Radar" Teubner (1994)

- C. A. Balanis, "Antenna Theory - Analysis and Design 3rd ed." Wiley-Interscience (2005)

- C. A. Balanis, "Advanced Engineering Electromagnetics" Wiley (1989)


Course L0784: Introduction To Antenna Theory
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L1349: Introduction To Antenna Theory
Typ Laboratory Course
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0785: Electromagnetic Waves

Courses
Title Typ Hrs/wk CP
Electromagnetic Waves (L0785) Lecture 2 3
Electromagnetic Waves (L0786) Recitation Section (large) 1 1
Electromagnetic Waves (L1346) Laboratory Course 1 2
Module Responsible Prof. Arne Jacob
Admission Requirements
Recommended Previous Knowledge

Electrical Engineering IV, Theoretical Electrical Engineering II, Microwave Engineering

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Based on Maxwell’s Equations the students are capable of computing field quantities of electromagnetic waves by means of scalar potentials. From these fields the students can then identify propagation characteristics and attenuation of electromagnetic waves on various structures. Furthermore, the students understand the effects of discontinuities on the propagation of modes and how these effects can be modelled by lumped equivalent circuits. The description of general microwave networks, as well as arbitrarily shaped cylindrical waveguides allow the students to account for and analyze a multitude of microwave problems. By means of perturbation and variational approaches the students are able to formulate problems such that the application to optimization processes or other numerical methods is possible. An easy final example gives the students a first glance at the method of moments that allows the solution of subject-specific problems on computers. In the laboratory experiments the theories presented in the lecture and the exercises are directly applied and quantified by small groups of students using measurements.

Skills

The students are capable of analyzing simple electromagnetic problems, as well as making qualitative statements about the effects on wave propagation. Basic effects of discontinuities, e.g. waveguide transitions, can be predicted and assessed. By means of the outlined methods the students are able to evaluate non-standard problems both qualitatively and quantitatively. Due to the generality of the covered approaches the students can link these methods with various classes of problems in order to develop intuitive solutions. In accompanying laboratory experiments the students have the opportunity to apply and verify the learned methods practically.

Personal Competence
Social Competence

The students work together in small groups in the course of the laboratory experiments on subject-specific tasks. The results are presented and documented in a professional manner.

Autonomy

The students are able to obtain additional information from given literature sources and set the content in context with the lecture. They can link and deepen their knowledge of other courses, e.g. Microwave Engineering and Theoretical Electrical Engineering II. The students obtain the ability to predict the behavior of electromagnetic components and to develop solutions in order to achieve a desired functionality. Both of these tasks can be done by the students in a self-contained way.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Course L0785: Electromagnetic Waves
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle SoSe
Content

- General properties of fields and plane waves: General solution of Maxwell’s Equations (in Cartesian coordinates), plane waves, rectangular waveguide, attenuation in waveguides, degenerate modes, cavity resonators, partially dielectrically filled rectangular wavguide, dielectric slab waveguide, surface waveguides, leaky waves.
- Field expansions: Modal expansions of rectangular waveguide and at waveguide transitions, field expansions in free space.
- Microwave circuits: cylindrical waveguides, N-port networks.
- Perturbation and variational approaches: Stationary formulas, Rayleigh-Ritz procedure, reaction concept.
- Method of moments: Formulation of problems, point matching, subsectional bases, approximate operators, Green’s functions, Application to scattering problems, wavelets as basis functions.

Literature

- H.-G. Unger, "Elektromagnetische Theorie für die Hochfrequenztechnik", Teil I+II, Teubner (1988)

- R. F. Harrington, "Time-Harmonic Electromagnetic Fields", Wiley-Interscience (1961

- R. F. Harrington, "Field Computation by Moment Methods", Robert E. Krieger Publ. Comp. (1968)

Course L0786: Electromagnetic Waves
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L1346: Electromagnetic Waves
Typ Laboratory Course
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0800: Numerical Methods for Electromagnetic Field Computation

Courses
Title Typ Hrs/wk CP
Numerical Methods for Electromagnetic Field Computation (L0802) Lecture 2 3
Numerical Methods for Electromagnetic Field Computation (L0803) Recitation Section (large) 1 1
Module Responsible Dr. Heinz-Dietrich Brüns
Admission Requirements

None

Recommended Previous Knowledge Basic principles of electromagnetic field theory
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Numerical methods in numerical field computation  are of increasing importance in electrical engineering, for example in the are of antenna development or for analyzing electromagnetic compatibility problems (EMC). The underlying principles of the major techniques that are currently applied in practice are explained. It turns out that each method has its strengths and weaknesses in relation to specific applications. The students shall be enabled to evaluate which kind of method could be advantageous for a certain case and if an application concerning a certain problem area is manageable at all.

Skills

The students will be able to set up discretized models based on the working principle of the chosen numerical method. This is carried out regarding the electrical size and considering the geometrical complexity. The students know the  interrelationship between the number of grid elements (surface patches, cells), the necessary memory resulting form this and the computation time. They are aware of the requirements of the method under consideration to achieve convergent results and they learn to validate these results using various techniques. The students are able to distinguish between methods that are used in the time domain, in the frequency domain and in the range of electrostatics. Furthermore the students know the advantages, possibilities and constraints of surface and volume based techniques.

Personal Competence
Social Competence

In practical exercises small groups of students can apply the program system CONCEPT-II, which is based on one of the most important techniques, the so-called method of moments. The program is under continuous development at the Institute of Electromagnetic Theory.

Autonomy

The students are able to generally apply their new knowledge in electromagnetics and to associate it with other courses. On the basis of the introduction given in the lecture they are capable to easily learn more about a technique from the given literature.

Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Oral exam
Examination duration and scale 30 Minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Course L0802: Numerical Methods for Electromagnetic Field Computation
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle SoSe
Content

-Short and in details more comprehensive repetition of relevant fields of electromagnetic theory
-Introduction into the finite difference method with emphasis on electrostatics and into the charge simulation method
-Basics of the boundary element method in electrostatics
-Hygens principle, magnetic currents in numerics
-FDTD, FIT (finite integration technique) as important techniques for time domain applications
-Finite element method (FEM)
-The method of moments in the frequency domain
-TLM in the time domain
-Possibilities for validating numerical solutions
-Application of hybrid techniques in special problem areas

Literature

Allen Tavlove, Susan C. Hagness: Computational Electrodynamics: The Finite-Difference
Time-Domain Method, Artech House Inc., 2005

Walton C. Gibson: The Method of Moments in Electromagnetics, Chapman & Hall/CRC

Ianming Jin: The Finite Element Method in Electromagnetics, John Wiley & Sons, Inc.,
second edition, 2002

Pei-bai Zhou: Numerical Analysis of Electromagnetic Fields, Springer-Verlag, 1993

C. Christopoulos: The Transmission-Line Modeling (TLM) Method in Electromagnetics,
Morgan&Claypool Publishers, 2006

Course L0803: Numerical Methods for Electromagnetic Field Computation
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle SoSe
Content

-Short and in details more comprehensive repetition of relevant fields of electromagnetic theory
-Introduction into the finite difference method with emphasis on electrostatics and into the charge simulation method
-Basics of the boundary element method in electrostatics
-Hygens principle, magnetic currents in numerics
-FDTD, FIT (finite integration technique) as important techniques for time domain applications
-Finite element method (FEM)
-The method of moments in the frequency domain
-TLM in the time domain
-Possibilities for validating numerical solutions
-Application of hybrid techniques in special problem areas

Literature

Allen Tavlove, Susan C. Hagness: Computational Electrodynamics: The Finite-Difference
Time-Domain Method, Artech House Inc., 2005

Walton C. Gibson: The Method of Moments in Electromagnetics, Chapman & Hall/CRC

Ianming Jin: The Finite Element Method in Electromagnetics, John Wiley & Sons, Inc.,
second edition, 2002

Pei-bai Zhou: Numerical Analysis of Electromagnetic Fields, Springer-Verlag, 1993

C. Christopoulos: The Transmission-Line Modeling (TLM) Method in Electromagnetics,
Morgan&Claypool Publishers, 2006

Module M0644: Optoelectronics II - Quantum Optics

Courses
Title Typ Hrs/wk CP
Optoelectronics II: Quantum Optics (L0360) Lecture 2 3
Optoelectronics II: Quantum Optics (Problem Solving Course) (L0362) Recitation Section (small) 1 1
Module Responsible Prof. Manfred Eich
Admission Requirements None
Recommended Previous Knowledge

Basic principles of electrodynamics, optics and quantum mechanics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the fundamental mathematical and physical relations of quantum optical phenomena such as absorption, stimulated and spontanous emission. They can describe material properties as well as technical solutions. They can give an overview on quantum optical components in technical applications.

Skills

Students can generate models and derive mathematical descriptions in relation to quantum optical phenomena and processes. They can derive approximative solutions and judge factors influential on the components' performance.


Personal Competence
Social Competence

Students can jointly solve subject related problems in groups. They can present their results effectively within the framework of the problem solving course.


Autonomy

Students are capable to extract relevant information from the provided references and to relate this information to the content of the lecture. They can reflect their acquired level of expertise with the help of lecture accompanying measures such as exam typical exam questions. Students are able to connect their knowledge with that acquired from other lectures.


Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Written exam
Examination duration and scale 40 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Materials Science: Specialisation Nano and Hybrid Materials: Elective Compulsory
Microelectronics and Microsystems: Specialisation Microelectronics Complements: Elective Compulsory
Course L0360: Optoelectronics II: Quantum Optics
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Manfred Eich
Language EN
Cycle WiSe
Content
  • Generation of light
  • Photons
  • Thermal and nonthermal light
  • Laser amplifier
  • Noise
  • Optical resonators
  • Spectral properties of laser light
  • CW-lasers (gas, solid state, semiconductor)
  • Pulsed lasers
Literature

Bahaa E. A. Saleh, Malvin Carl Teich, Fundamentals of Photonics, Wiley 2007
Demtröder, W., Laser Spectroscopy: Basic Concepts and Instrumentation, Springer, 2002
Kasap, S.O., Optoelectronics and Photonics: Principles and Practices, Prentice Hall, 2001
Yariv, A., Quantum Electronics, Wiley, 1988
Wilson, J., Hawkes, J., Optoelectronics: An Introduction, Prentice Hall, 1997, ISBN: 013103961X
Siegman, A.E., Lasers, University Science Books, 1986

Course L0362: Optoelectronics II: Quantum Optics (Problem Solving Course)
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Manfred Eich
Language EN
Cycle WiSe
Content see lecture Optoelectronics 1 - Wave Optics
Literature

see lecture Optoelectronics 1 - Wave Optics

Module M0666: Seminar on Electromagnetic Compatibility and Electrical Power Systems

Courses
Title Typ Hrs/wk CP
Seminar on Electromagnetic Compatibility and Electrical Power Systems (L0409) Seminar 2 2
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge

Fundamentals of electrical engineering


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students know current research topics in the fields of electromagnetic compatibility, theory of electromagnetic fields, and electrical power systems. They are able to use professional language in discussions. They are able to explain research topics.


Skills

Students are able to gain knowledge about a new field by themselves. In order to do that they make use of their existing knowledge and try to connect it with the topics of the new field. They close their knowledge gaps by discussing with research assistants and by their own literature and internet search. They are capable of summarizing and presenting scientific publications.  


Personal Competence
Social Competence

In cooperation with research assistants students are able to familiarize themselves with and discuss with others current research topics. They are capable of drafting, presenting, and explaining summaries of these topics in English in front of a professional audience.


Autonomy

Students are capable of gathering information from subject related, professional publications and relate that information to the context of the seminar. They are able to find on their own new sources in the Internet. They are able to make a connection with the subject of their chosen specialization.


Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Presentation
Examination duration and scale 20-30 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Course L0409: Seminar on Electromagnetic Compatibility and Electrical Power Systems
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Christian Schuster, Prof. Frank Gronwald, Prof. Christian Becker
Language EN
Cycle WiSe/SoSe
Content

Current research topics in the fields electromagnetic compatibility, theory of electromagnetic fields, and electrical power systems




Literature

Aktuelle Literatur zu Forschungsthemen aus der elektromagnetischen Verträglichkeit, der theoretischen Elektrotechnik und der elektrischen Energiesystemtechnik / Current literature with regard to research topics in the fields of electromagnetic compatibility, theory of electromagnetic fields, and and electrical power systems







Module M0795: Research Project in Microwave Engineering, Optics and Electromagnetic Compatibility

Courses
Title Typ Hrs/wk CP
Module Responsible Dozenten des SD E
Admission Requirements None
Recommended Previous Knowledge

Advanced state of knowledge in the electrical engineering master program

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students know current research topics oft institutes engaged in their specialization. They can name the fundamental scientific methods used for doing related reserach.


Skills

Strudents are capable of completing a small, independent sub-project of currently ongoing research projects in the institutes engaged in their specialization. Students can justify and explain their approach for problem solving, they can draw conclusions from their results, and then can find new ways and methods for their work. Students are capable of comparing and assessing alterantive approaches with their own with regard to given criteria.

Personal Competence
Social Competence

Students are able to discuss their work progress with research assistants of the supervising institute .  They are capable of presenting their results in front of a professional audience.


Autonomy

Based on their competences gained so far students are capable of defining meaningful tasks within ongoing research project for themselves. They are able to develop the necessary understanding  and problem solving methods.


Workload in Hours Independent Study Time 180, Study Time in Lecture 0
Credit points 6
Examination Project (accord. to Subject Specific Regulations)
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory

Module M1243: Seminar on Microwave Engineering

Courses
Title Typ Hrs/wk CP
Seminar on Microwave Engineering (L1689) Seminar 2 2
Module Responsible Prof. Arne Jacob
Admission Requirements None
Recommended Previous Knowledge

Fundamentals of communication engineering, semiconductor devices and circuits. Basics of Wave propagation from transmission line theory and theoretical electrical engineering.

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the most important facts and relationships of a specific topic from the field of high-frequency technology.

Skills

Students are able to compile a specified topic from the field of high-frequency technology and to give a clear, structured and comprehensible presentation of the subject.

Personal Competence
Social Competence

Students are able to adapt their presentation with respect to content, detailedness, and presentation style to the composition and previous knowledge of the audience. They can answer questions from the audience in a curt and precise manner. 

Autonomy

Students are able to autonomously carry out a literature research concerning a given topic. They can independently evaluate the material. They can self-reliantly decide which parts of the material should be included in the presentation.

Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Presentation
Examination duration and scale 30 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Course L1689: Seminar on Microwave Engineering
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Arne Jacob
Language EN
Cycle WiSe/SoSe
Content

Seminar talk on a given subject


Literature

Themenabhängig / subject related


Module M0781: EMC II: Signal Integrity and Power Supply of Electronic Systems

Courses
Title Typ Hrs/wk CP
EMC II: Signal Integrity and Power Supply of Electronic Systems (L0770) Lecture 3 4
EMC II: Signal Integrity and Power Supply of Electronic Systems (L0771) Recitation Section (small) 1 1
EMC II: Signal Integrity and Power Supply of Electronic Systems (L0774) Laboratory Course 1 1
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge

Fundamentals of electrical engineering


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain the fundamental principles, inter-dependencies, and methods of signal and power integrity of electronic systems. They are able to relate signal and power integrity to the context of interference-free design of such systems, i.e. their electromagnetic compatibility. They are capable of explaining the basic behavior of signals and power supply in typical packages and interconnects. They are able to propose and describe problem solving strategies for signal and power integrity issues. They are capable of giving an overview over measurement and simulation methods for characterization of signal and power integrity in electrical engineering practice.


Skills

Students are able to apply a series of modeling methods for characterization of electromagnetic field behavior in packages and interconnect structure of electronic systems. They are able to determine the most important effects that these models are predicting in terms of signal and power integrity. They can classify these effects and they can quantitatively analyze them. They are capable of deriving problem solving strategies from these predictions and they can adapt them to applications in electrical engineering practice. The can evaluate their problem solving strategies against each other.


Personal Competence
Social Competence

Students are able to work together on subject related tasks in small groups. They are able to present their results effectively in English (e.g. during CAD exercises).


Autonomy

Students are capable to gather necessary information from the references provided and relate that information to the context of the lecture. They are able to make a connection between their knowledge obtained in this lecture with the content of other lectures (e.g. theory of electromagnetic fields, communications, and semiconductor circuit design). They can communicate problems and solutions in the field of signal integrity and power supply of interconnect and packages in English.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Oral exam
Examination duration and scale 30-60 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Course L0770: EMC II: Signal Integrity and Power Supply of Electronic Systems
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle WiSe
Content

- The role of packages and interconnects in electronic systems

- Components of packages and interconnects in electronic systems

- Main goals and concepts of signal and power integrity of electronic systems

- Repeat of relevant concepts from the theory electromagnetic fields

- Properties of digital signals and systems

- Design and characterization of signal integrity

- Design and characterization of power supply

- Techniques and devices for measurements in time- and frequency-domain

- CAD tools for electrical analysis and design of packages and interconnects

- Connection to overall electromagnetic compatibility of electronic systems


Literature

- J. Franz, "EMV: Störungssicherer Aufbau elektronischer Schaltungen", Springer (2012)

- R. Tummala, "Fundamentals of Microsystems Packaging", McGraw-Hill (2001)

- S. Ramo, J. Whinnery, T. Van Duzer, "Fields and Waves in Communication Electronics", Wiley (1994)

- S. Thierauf, "Understanding Signal Integrity", Artech House (2010)

- M. Swaminathan, A. Engin, "Power Integrity Modeling and Design for Semiconductors and Systems", Prentice-Hall (2007)


Course L0771: EMC II: Signal Integrity and Power Supply of Electronic Systems
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0774: EMC II: Signal Integrity and Power Supply of Electronic Systems
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle WiSe
Content

- The role of packages and interconnects in electronic systems

- Components of packages and interconnects in electronic systems

- Main goals and concepts of signal and power integrity of electronic systems

- Repeat of relevant concepts from the theory electromagnetic fields

- Properties of digital signals and systems

- Design and characterization of signal integrity

- Design and characterization of power supply

- Techniques and devices for measurements in time- and frequency-domain

- CAD tools for electrical analysis and design of packages and interconnects

- Connection to overall electromagnetic compatibility of electronic systems


Literature

- J. Franz, "EMV: Störungssicherer Aufbau elektronischer Schaltungen", Springer (2012)

- R. Tummala, "Fundamentals of Microsystems Packaging", McGraw-Hill (2001)

- S. Ramo, J. Whinnery, T. Van Duzer, "Fields and Waves in Communication Electronics", Wiley (1994)

- S. Thierauf, "Understanding Signal Integrity", Artech House (2010)

- M. Swaminathan, A. Engin, "Power Integrity Modeling and Design for Semiconductors and Systems", Prentice-Hall (2007)


Module M0788: Microwave Semiconductor Devices and Circuits II

Courses
Title Typ Hrs/wk CP
Microwave Semiconductor Devices and Circuits II (L0788) Lecture 1 1
Microwave Semiconductor Devices and Circuits II (L0789) Recitation Section (large) 1 1
Microwave Circuit Design Laboratory (L0790) Laboratory Course 4 4
Module Responsible Prof. Arne Jacob
Admission Requirements None
Recommended Previous Knowledge

Fundamentals of Semiconductor Technology, Microwave Engineering, Microwave Semiconductor Devices and Circuits I


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are capable of explaining the functionality of frequency multipliers in detail. They can present theories, concepts, and reasonable assumptions for description and synthesis. They are able to apply indepth knowledge on semiconductor physics of selected microwave devices to the frequency multiplier. Students can describe microwave measurement methods.


Skills

The students can assess effects occurring in active microwave circuits and are capable of analyzing and evaluating them. They are able to design and realize linear and nonlinear microwave circuits with help of modern software tools, taking application and manufacturing requirements into account. They are able to select and apply suitable measurement techniques.


Personal Competence
Social Competence

The students are able to carry out subject-specific tasks in small groups, and to adequately present solutions (e.g. in microwave circuit design laboratory). They are capable of assessing and reflecting their contribution to the overall project (satellite receiver). They are able to communicate with different groups and with a supervisor, and to handle feedback on their own performance constructively.


Autonomy

The students are able to obtain additional information from given literature sources and set the content in context with the lecture. They can link and deepen their knowledge of other courses and translate their knowledge to practical situation. The students acquire the ability to communicate problems and solutions in the field of microwave semiconductor devices and circuits in English. They can assess their abilities and results of their work and evaluate the necessity of support.


Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Course L0788: Microwave Semiconductor Devices and Circuits II
Typ Lecture
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle WiSe
Content

- Frequency multiplier: Harmonic balance, noise in nonlinear circuits; Step Recovery Diode, FET; circuit synthesis, large signal, noise, and stability analysis

- Low Noise Amplifier (LNA) circuit design: Stability and stability circles, gain and gain circles, noise, noise figure and noise figure circles

- Mixer, oscillator: Measurement techniques (Network analyzer, Spectrum analyzer, Frequency generator)


Literature

- E. Voges, „Hochfrequenztechnik“, Hüthig (2004)

- H.-G. Unger, W. Harth, „Hochfrequenz-Halbleiterelektronik“, S. Hirzel Verlag (1972)


- S.M. Sze, "Physics of Semiconductor Devices", John Wiley & Sons (1981)

- A. Jacob, "Lecture Notes Microwave Semiconductor Devices and Circuits Part II"


Course L0789: Microwave Semiconductor Devices and Circuits II
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0790: Microwave Circuit Design Laboratory
Typ Laboratory Course
Hrs/wk 4
CP 4
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
Lecturer Prof. Arne Jacob
Language DE/EN
Cycle WiSe
Content

- Satellite receiver at X-Band (low noise amplifier, mixer, oscillator): Circuit and system design, realization, and characterization

Literature

- A. Jacob, "Microwave Circuit Design Laboratory Guide"


Specialization Medical Technology


The specialization ‚Medical Technology‘ offers students the opportunity to put an interdisciplinary focus in their studies. On the one hand, a series of technical modules foster an in-depth understanding of modern medical technology, particularly with respect to electrical engineering. On the other hand, modules on medical topics provide insight into clinical problems, environments and terminology. Students will be able to design, implement, and evaluate methods, algorithms and systems in the context of clinical scenarios. The assessment will be based on their knowledge of the complex system ‘patient’. Hence, competencies developed in this specialization at the interface between electrical engineering and medicine prepare students for positions in industry and academia.

Module M0548: Bioelectromagnetics: Principles and Applications

Courses
Title Typ Hrs/wk CP
Bioelectromagnetics: Principles and Applications (L0371) Lecture 3 5
Bioelectromagnetics: Principles and Applications (L0373) Recitation Section (small) 2 1
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge

Basic principles of physics


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the basic principles, relationships, and methods of bioelectromagnetics, i.e. the quantification and application of electromagnetic fields in biological tissue. They can define and exemplify the most important physical phenomena and order them corresponding to wavelength and frequency of the fields. They can give an overview over measurement and numerical techniques for characterization of electromagnetic fields in practical applications . They can give examples for therapeutic and diagnostic utilization of electromagnetic fields in medical technology.


Skills

Students know how to apply various methods to characterize the behavior of electromagnetic fields in biological tissue.  In order to do this they can relate to and make use of the elementary solutions of Maxwell’s Equations. They are able to assess the most important effects that these models predict for biological tissue, they can order the effects corresponding to wavelength and frequency, respectively, and they can analyze them in a quantitative way. They are able to develop validation strategies for their predictions. They are able to evaluate the effects of electromagnetic fields for therapeutic and diagnostic applications and make an appropriate choice.


Personal Competence
Social Competence

Students are able to work together on subject related tasks in small groups. They are able to present their results effectively in English (e.g. during small group exercises).


Autonomy

Students are capable to gather information from subject related, professional publications and relate that information to the context of the lecture. They are able to make a connection between their knowledge obtained in this lecture with the content of other lectures (e.g. theory of electromagnetic fields, fundamentals of electrical engineering / physics). They can communicate problems and effects in the field of bioelectromagnetics in English.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Oral exam
Examination duration and scale 30-60 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Course L0371: Bioelectromagnetics: Principles and Applications
Typ Lecture
Hrs/wk 3
CP 5
Workload in Hours Independent Study Time 108, Study Time in Lecture 42
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle SoSe
Content

- Fundamental properties of electromagnetic fields (phenomena)

- Mathematical description of electromagnetic fields (Maxwell’s Equations)

- Electromagnetic properties of biological tissue

- Principles of energy absorption in biological tissue, dosimetry

- Numerical methods for the computation of electromagnetic fields (especially FDTD)

- Measurement techniques for characterization of electromagnetic fields

- Behavior of electromagnetic fields of low frequency in biological tissue

- Behavior of electromagnetic fields of medium frequency in biological tissue

- Behavior of electromagnetic fields of high frequency in biological tissue

- Behavior of electromagnetic fields of very high frequency in biological tissue

- Diagnostic applications of electromagnetic fields in medical technology

- Therapeutic applications of electromagnetic fields in medical technology

- The human body as a generator of electromagnetic fields


Literature

- C. Furse, D. Christensen, C. Durney, "Basic Introduction to Bioelectromagnetics", CRC (2009)

- A. Vorst, A. Rosen, Y. Kotsuka, "RF/Microwave Interaction with Biological Tissues", Wiley (2006)

- S. Grimnes, O. Martinsen, "Bioelectricity and Bioimpedance Basics", Academic Press (2008)

- F. Barnes, B. Greenebaum, "Bioengineering and Biophysical Aspects of Electromagnetic Fields", CRC (2006)


Course L0373: Bioelectromagnetics: Principles and Applications
Typ Recitation Section (small)
Hrs/wk 2
CP 1
Workload in Hours Independent Study Time 2, Study Time in Lecture 28
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle SoSe
Content

- Fundamental properties of electromagnetic fields (phenomena)

- Mathematical description of electromagnetic fields (Maxwell’s Equations)

- Electromagnetic properties of biological tissue

- Principles of energy absorption in biological tissue, dosimetry

- Numerical methods for the computation of electromagnetic fields (especially FDTD)

- Measurement techniques for characterization of electromagnetic fields

- Behavior of electromagnetic fields of low frequency in biological tissue

- Behavior of electromagnetic fields of medium frequency in biological tissue

- Behavior of electromagnetic fields of high frequency in biological tissue

- Behavior of electromagnetic fields of very high frequency in biological tissue

- Diagnostic applications of electromagnetic fields in medical technology

- Therapeutic applications of electromagnetic fields in medical technology

- The human body as a generator of electromagnetic fields


Literature

- C. Furse, D. Christensen, C. Durney, "Basic Introduction to Bioelectromagnetics", CRC (2009)

- A. Vorst, A. Rosen, Y. Kotsuka, "RF/Microwave Interaction with Biological Tissues", Wiley (2006)

- S. Grimnes, O. Martinsen, "Bioelectricity and Bioimpedance Basics", Academic Press (2008)

- F. Barnes, B. Greenebaum, "Bioengineering and Biophysical Aspects of Electromagnetic Fields", CRC (2006)


Module M0630: Robotics and Navigation in Medicine

Courses
Title Typ Hrs/wk CP
Robotics and Navigation in Medicine (L0335) Lecture 2 3
Robotics and Navigation in Medicine (L0338) Project Seminar 2 2
Robotics and Navigation in Medicine (L0336) Recitation Section (small) 1 1
Module Responsible Prof. Alexander Schlaefer
Admission Requirements

None

Recommended Previous Knowledge
  • principles of math (algebra, analysis/calculus)
  • principles of programming, e.g., in Java or C++
  • solid R or Matlab skills
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students can explain kinematics and tracking systems in clinical contexts and illustrate systems and their components in details. Systems can be evaluated with respect to collision detection and  safety and regulations. Students can assess typical systems regarding design and  limitations.

Skills

The students are able to design and evaluate navigation systems and robotic systems for medical applications.


Personal Competence
Social Competence

The students discuss the results of other groups, provide helpful feedback and can incoorporate feedback into their work.

Autonomy

The students can reflect their knowledge and document the results of their work. They can present the results in an appropriate manner.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Product Development, Materials and Production: Specialisation Product Development: Elective Compulsory
Product Development, Materials and Production: Specialisation Production: Elective Compulsory
Product Development, Materials and Production: Specialisation Materials: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory
Course L0335: Robotics and Navigation in Medicine
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle SoSe
Content

- kinematics
- calibration
- tracking systems
- navigation and image guidance
- motion compensation
The seminar extends and complements the contents of the lecture with respect to recent research results.


Literature

Spong et al.: Robot Modeling and Control, 2005
Troccaz: Medical Robotics, 2012
Further literature will be given in the lecture.

Course L0338: Robotics and Navigation in Medicine
Typ Project Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L0336: Robotics and Navigation in Medicine
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0635: Medical Technology Lab

Courses
Title Typ Hrs/wk CP
Medical Technology Lab (L1096) Problem-based Learning 6 6
Module Responsible Prof. Alexander Schlaefer
Admission Requirements

good programming skills

Recommended Previous Knowledge

sound programming skills (Java / C++)
skills in R/Matlab
knowledge of image processing
principles of math (algebra, analysis/calculus)
principles of  stochastics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students recognize the complexity of medical technology and can explain, which methods are appropriate to solve a problem at hand.

Skills

The students are able to analyze and solve problems in medical technology.


Personal Competence
Social Competence

The students can define project aims and scope and organize the project as team work. They can present their results in an appropriate manner.

Autonomy

The students take responsibility for their tasks and coordinate their individual work with other group members.  They deliver their work on time. They independently acquire additional knowledge by doing a specific literature research.

Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Credit points 6
Examination Written elaboration
Examination duration and scale approx. 8 pages, time frame: over the course of the semester
Assignment for the Following Curricula Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Course L1096: Medical Technology Lab
Typ Problem-based Learning
Hrs/wk 6
CP 6
Workload in Hours Independent Study Time 96, Study Time in Lecture 84
Lecturer Prof. Alexander Schlaefer
Language DE/EN
Cycle SoSe
Content

The actual project topic will be defined as part of the project.

Literature

Wird in der Veranstaltung bekannt gegeben.

Module M0811: Medical Imaging Systems

Courses
Title Typ Hrs/wk CP
Medical Imaging Systems (L0819) Lecture 4 6
Module Responsible Dr. Michael Grass
Admission Requirements none
Recommended Previous Knowledge none
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can:

  • Describe the system configuration and components of the main clinical imaging systems;
  • Explain how the system components and the overall system of the imaging systems function;
  • Explain and apply the physical processes that make imaging possible and use with the fundamental physical equations; 
  • Name and describe the physical effects required to generate image contrasts; 
  • Explain how spatial and temporal resolution can be influenced and how to characterize the images generated;
  • Explain which image reconstruction methods are used to generate images;

Describe and explain the main clinical uses of the different systems.

Skills

Students are able to: 

  • Explain the physical processes of images and assign to the systems the basic mathematical or physical equations required;
    • Calculate the parameters of imaging systems using the mathematical or physical equations;
    • Determine the influence of different system components on the spatial and temporal resolution of imaging systems;
    • Explain the importance of different imaging systems for a number of clinical applications;

Select a suitable imaging system for an application.

Personal Competence
Social Competence none
Autonomy

Students can:

  • Understand which physical effects are used in medical imaging;
  • Decide independently for which clinical issue a measuring system can be used.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Biomedical Engineering: Core qualification: Compulsory
Product Development, Materials and Production: Specialisation Product Development: Elective Compulsory
Product Development, Materials and Production: Specialisation Production: Elective Compulsory
Product Development, Materials and Production: Specialisation Materials: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0819: Medical Imaging Systems
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Dr. Michael Grass, Dr. Tim Nielsen, Dr. Sven Prevrhal, Frank Michael Weber
Language DE
Cycle SoSe
Content
Literature

Primary book:

1. P. Suetens, "Fundamentals of Medical Imaging", Cambridge Press

Secondary books:

- A. Webb, "Introduction to Biomedical Imaging", IEEE Press 2003.

- W.R. Hendee and E.R. Ritenour, "Medical Imaging Physics", Wiley-Liss, New York, 2002.

- H. Morneburg (Edt), "Bildgebende Systeme für die medizinische Diagnostik", Erlangen: Siemens Publicis MCD Verlag, 1995.

- O. Dössel, "Bildgebende Verfahren in der Medizin", Springer Verlag Berlin, 2000.

Module M0845: Feedback Control in Medical Technology

Courses
Title Typ Hrs/wk CP
Feedback Control in Medical Technology (L0664) Lecture 2 3
Module Responsible Prof. Olaf Simanski
Admission Requirements
Recommended Previous Knowledge

Basics in Control, Basics in Physiology

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The lecture will introduce into the fascinating area of medical technology with the engineering point of view. Fundamentals in human physiology will be similarly introduced like knowledge in control theory.

Internal control loops of the human body will be discussed in the same way like the design of external closed loop system fo example in for anesthesia control.

The handling of PID controllers and modern controller like predictive controller or fuzzy controller or neural networks will be illustrated. The operation of simple equivalent circuits will be discussed.

Skills

Application of modeling, identification, control technology in the field of medical technology.


Personal Competence
Social Competence

Students can develop solutions to specific problems in small groups and present their results (e.g. during project week)

Autonomy

Students are able to find necessary literature and to set it into the context of the lecture. They are able to continuously evaluate their knowledge and to take control of their learning process. They can combine knowledge from different courses to form a consistent whole.

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Examination Oral exam
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Course L0664: Feedback Control in Medical Technology
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Ulf Pilz, Prof. Olaf Simanski
Language DE
Cycle SoSe
Content

Taking an engineering point of view, the lecture is structured as follows.

  • Introduction to the topic with selected examples
  • Physiology - introduction and overview
  • Regeneration of functions of the cardiovascular system
  • Regeneration of the respiratory functions
  • Closed loop control in anesthesia
  • regeneration of kidney and liver functions
  • regeneration of motorize function/ rehabilitation engineering 
  • navigation systems and robotic in medicine

 The lecture will use knowledge from modeling, simulation and controller design and MATLAB and SIMULINK will be used.


Literature

Silbernagel/Depopoulos: Taschenatlas der Physiologie, Thieme Verlag Stuttgart

Werner: Kooperative und autonome Systeme der Medizintechnik, Oldenburg Verlag

M.C.K.Khoo:“Physiological Control System“, IEEE Press, 2000

Module M1277: MED I: Introduction to Anatomy

Courses
Title Typ Hrs/wk CP
Introduction to Anatomy (L0384) Lecture 2 3
Module Responsible Prof. Udo Schumacher
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students can describe

basal structures and functions of internal organs and the musculoskeletal system

.

The students can describe the basic macroscopy and microscopy of those systems.

Skills

The students can recognize the relationship between given anatomical facts and the development of common diseases; they can explain the relevance of structures and their functions in the context of widespread diseases.

Personal Competence
Social Competence

The students can participate in current discussions in biomedical research and medicine on a professional level.

Autonomy

The students are able to access anatomical knowledge by themselves, can participate competently in conversations on the topic and acquire the relevant knowledge themselves.

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Mechanical Engineering: Specialisation Biomechanics: Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0384: Introduction to Anatomy
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Lange
Language DE
Cycle SoSe
Content

General Anatomy

1st week:             The Eucaryote Cell

2nd week:             The Tissues

3rd week:             Cell Cycle, Basics in Development

4th week:             Musculoskeletal System

5th week:             Cardiovascular System

6th week:             Respiratory System   

7th week:             Genito-urinary System

8th week:             Immune system

9th week:             Digestive System I

10th week:           Digestive System II

11th week:           Endocrine System

12th week:           Nervous System

13th week:           Exam



Literature

Adolf Faller/Michael Schünke, Der Körper des Menschen, 16. Auflage, Thieme Verlag Stuttgart, 2012

Module M1280: MED II: Introduction to Physiology

Courses
Title Typ Hrs/wk CP
Introduction to Physiology (L0385) Lecture 2 3
Module Responsible Dr. Roger Zimmermann
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students can


  • describe the basics of the energy metabolism;
  • describe physiological connections in select fields of muscle, heart/circulation, neuro- and sensory physiology.
Skills

The students can

  • describe the effects of basic bodily functions (sensory, transmission and processing of information, development of forces and vital functions) and relate them to similar technical systems.
Personal Competence
Social Competence

The students can conduct discussions in research and medicine on a technical level.

The students can find solutions to problems in the field of physiology, both analytical and metrological

Autonomy

The students can develop understanding of topics from the course, using technical literature, by themselves

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Examination Written exam
Examination duration and scale 60 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Mechanical Engineering: Specialisation Biomechanics: Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0385: Introduction to Physiology
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Roger Zimmermann
Language DE
Cycle SoSe
Content
Literature

Taschenatlas der Physiologie, Silbernagl Despopoulos, ISBN 978-3-135-67707-1, Thieme

Repetitorium Physiologie, Speckmann, ISBN 978-3-437-42321-5, Elsevier

Module M1278: MED I: Introduction to Radiology and Radiation Therapy

Courses
Title Typ Hrs/wk CP
Introduction to Radiology and Radiation Therapy (L0383) Lecture 2 3
Module Responsible Prof. Ulrich Carl
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Therapy

The students can distinguish different types of currently used equipment with respect to its use in radiation therapy.

The students can explain complex treatment plans used in radiation therapy in interdisciplinary contexts (e.g. surgery, internal medicine).

The students can describe the patients' passage from their initial admittance through to follow-up care.

Diagnostics

The students can illustrate the technical base concepts of projection radiography, including angiography and mammography, as well as sectional imaging techniques (CT, MRT, US).

The students can explain the diagnostic as well as therapeutic use of imaging techniques, as well as the technical basis for those techniques.

The students can choose the right treatment method depending on the patient's clinical history and needs.

The student can explain the influence of technical errors on the imaging techniques.

The student can draw the right conclusions based on the images' diagnostic findings or the error protocol.

Skills

Therapy

The students can distinguish curative and palliative situations and motivate why they came to that conclusion.

The students can develop adequate therapy concepts and relate it to the radiation biological aspects.

The students can use the therapeutic principle (effects vs adverse effects)

The students can distinguish different kinds of radiation, can choose the best one depending on the situation (location of the tumor) and choose the energy needed in that situation (irradiation planning).

The student can assess what an individual psychosocial service should look like (e.g. follow-up treatment, sports, social help groups, self-help groups, social services, psycho-oncology).

Diagnostics

The students can suggest solutions for repairs of imaging instrumentation after having done error analyses.

The students can classify results of imaging techniques according to different groups of diseases based on their knowledge of anatomy, pathology and pathophysiology.

Personal Competence
Social Competence

The students can assess the special social situation of tumor patients and interact with them in a professional way.

The students are aware of the special, often fear-dominated behavior of sick people caused by diagnostic and therapeutic measures and can meet them appropriately.

Autonomy

The students can apply their new knowledge and skills to a concrete therapy case.

The students can introduce younger students to the clinical daily routine.

The students are able to access anatomical knowledge by themselves, can participate competently in conversations on the topic and acquire the relevant knowledge themselves.

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Mechanical Engineering: Specialisation Biomechanics: Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0383: Introduction to Radiology and Radiation Therapy
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Ulrich Carl, Prof. Thomas Vestring
Language DE
Cycle SoSe
Content

The students will be given an understanding of the technological possibilities in the field of medical imaging, interventional radiology and radiation therapy/radiation oncology. It is assumed, that students in the beginning of the course have heard the word “X-ray” at best. It will be distinguished between the two arms of diagnostic (Prof. Dr. med. Thomas Vestring) and therapeutic (Prof. Dr. med. Ulrich Carl) use of X-rays. Both arms depend on special big units, which determine a predefined sequence in their respective departments



Literature
  • "Technik der medizinischen Radiologie"  von T. + J. Laubenberg –

    7. Auflage – Deutscher Ärzteverlag –  erschienen 1999

  • "Klinische Strahlenbiologie" von Th. Herrmann, M. Baumann und W. Dörr –

    4. Auflage - Verlag Urban & Fischer –  erschienen 02.03.2006

    ISBN: 978-3-437-23960-1

  • "Strahlentherapie und Onkologie für MTA-R" von R. Sauer –

             5. Auflage 2003 - Verlag Urban & Schwarzenberg – erschienen 08.12.2009

             ISBN: 978-3-437-47501-6

  • "Taschenatlas der Physiologie" von S. Silbernagel und A. Despopoulus‑                

    8. Auflage – Georg Thieme Verlag - erschienen 19.09.2012

    ISBN: 978-3-13-567708-8

  • "Der Körper des Menschen " von A. Faller  u. M. Schünke -

    16. Auflage 2004 – Georg Thieme Verlag –  erschienen 18.07.2012

    ISBN: 978-3-13-329716-5

  • „Praxismanual Strahlentherapie“ von Stöver / Feyer –

    1. Auflage - Springer-Verlag GmbH –  erschienen 02.06.2000



Module M1325: Seminar Medical Technology

Courses
Title Typ Hrs/wk CP
Seminar Medical Technology (L1830) Seminar 2 2
Module Responsible Prof. Alexander Schlaefer
Admission Requirements None
Recommended Previous Knowledge Engineering / Mathematics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Review of a recent scientific publication
Skills

Reviewing of a scientific publications

Personal Competence
Social Competence presentation skills
Autonomy Consider the publication in the context of the student's knowledge
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Presentation
Examination duration and scale 20-30 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Course L1830: Seminar Medical Technology
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe/SoSe
Content We are considering recent scientific publications in the field of medical technology. Students will review a paper and discuss it's merits in the context of the state of the art. The key methods and results will be presented in a talk. Students will critically acclaim the authors contribution.
Literature TBD

Module M0550: Digital Image Analysis

Courses
Title Typ Hrs/wk CP
Digital Image Analysis (L0126) Lecture 4 6
Module Responsible Prof. Rolf-Rainer Grigat
Admission Requirements None
Recommended Previous Knowledge

System theory of one-dimensional signals (convolution and correlation, sampling theory, interpolation and decimation, Fourier transform, linear time-invariant systems), linear algebra (Eigenvalue decomposition, SVD), basic stochastics and statistics (expectation values, influence of sample size, correlation and covariance, normal distribution and its parameters), basics of Matlab, basics in optics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can

  • Describe imaging processes
  • Depict the physics of sensorics
  • Explain linear and non-linear filtering of signals
  • Establish interdisciplinary connections in the subject area and arrange them in their context
  • Interpret effects of the most important classes of imaging sensors and displays using mathematical methods and physical models.


Skills

Students are able to

  • Use highly sophisticated methods and procedures of the subject area
  • Identify problems and develop and implement creative solutions.

Students can solve simple arithmetical problems relating to the specification and design of image processing and image analysis systems.

Students are able to assess different solution approaches in multidimensional decision-making areas.

Students can undertake a prototypical analysis of processes in Matlab.


Personal Competence
Social Competence k.A.


Autonomy

Students can solve image analysis tasks independently using the relevant literature.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 60 Minutes, Content of Lecture and materials in StudIP
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0126: Digital Image Analysis
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Rolf-Rainer Grigat
Language EN
Cycle WiSe
Content
  • Image representation, definition of images and volume data sets, illumination, radiometry, multispectral imaging, reflectivities, shape from shading
  • Perception of luminance and color, color spaces and transforms, color matching functions, human visual system, color appearance models
  • imaging sensors (CMOS, CCD, HDR, X-ray, IR), sensor characterization(EMVA1288), lenses and optics
  • spatio-temporal sampling (interpolation, decimation, aliasing, leakage, moiré, flicker, apertures)
  • features (filters, edge detection, morphology, invariance, statistical features, texture)
  • optical flow ( variational methods, quadratic optimization, Euler-Lagrange equations)
  • segmentation (distance, region growing, cluster analysis, active contours, level sets, energy minimization and graph cuts)
  • registration (distance and similarity, variational calculus, iterative closest points)
Literature

Bredies/Lorenz, Mathematische Bildverarbeitung, Vieweg, 2011
Wedel/Cremers, Stereo Scene Flow for 3D Motion Analysis, Springer 2011
Handels, Medizinische Bildverarbeitung, Vieweg, 2000
Pratt, Digital Image Processing, Wiley, 2001
Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1989

Module M0623: Intelligent Systems in Medicine

Courses
Title Typ Hrs/wk CP
Intelligent Systems in Medicine (L0331) Lecture 2 3
Intelligent Systems in Medicine (L0334) Project Seminar 2 2
Intelligent Systems in Medicine (L0333) Recitation Section (small) 1 1
Module Responsible Prof. Alexander Schlaefer
Admission Requirements None
Recommended Previous Knowledge
  • principles of math (algebra, analysis/calculus)
  • principles of stochastics
  • principles of programming, Java/C++ and R/Matlab
  • advanced programming skills
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are able to analyze and solve clinical treatment planning and decision support problems using methods for search, optimization, and planning. They are able to explain methods for classification and their respective advantages and disadvantages in clinical contexts. The students can compare  different methods for representing medical knowledge. They can evaluate methods in the context of clinical data  and explain challenges due to the clinical nature of the data and its acquisition and due to privacy and safety requirements.

Skills

The students can give reasons for selecting and adapting methods for classification, regression, and prediction. They can assess the methods based on actual patient data and evaluate the implemented methods.

Personal Competence
Social Competence

The students discuss the results of other groups, provide helpful feedback and can incoorporate feedback into their work.

Autonomy

The students can reflect their knowledge and document the results of their work. They can present the results in an appropriate manner.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0331: Intelligent Systems in Medicine
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content

- methods for search, optimization,  planning,  classification, regression and prediction in a clinical context
- representation of medical knowledge
- understanding challenges due to clinical and patient related data and data acquisition
The students will work in groups to apply the methods introduced during the lecture using problem based learning.


Literature

Russel & Norvig: Artificial Intelligence: a Modern Approach, 2012
Berner: Clinical Decision Support Systems: Theory and Practice, 2007
Greenes: Clinical Decision Support: The Road Ahead, 2007
Further literature will be given in the lecture


Course L0334: Intelligent Systems in Medicine
Typ Project Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0333: Intelligent Systems in Medicine
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0768: Microsystems Technology in Theory and Practice

Courses
Title Typ Hrs/wk CP
Microsystems Technology (L0724) Lecture 2 4
Microsystems Technology (L0725) Problem-based Learning 2 2
Module Responsible Prof. Hoc Khiem Trieu
Admission Requirements None
Recommended Previous Knowledge

Basics in physics, chemistry, mechanics and semiconductor technology

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able

     to present and to explain current fabrication techniques for microstructures and especially methods for the fabrication of microsensors and microactuators, as well as the integration thereof in more complex systems

     to explain in details operation principles of microsensors and microactuators and

     to discuss the potential and limitation of microsystems in application.


Skills

Students are capable

     to analyze the feasibility of microsystems,

     to develop process flows for the fabrication of microstructures and

     to apply them.




Personal Competence
Social Competence


Students are able to prepare and perform their lab experiments in team work as well as to present and discuss the results in front of audience.


Autonomy

None

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0724: Microsystems Technology
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Hoc Khiem Trieu
Language EN
Cycle WiSe
Content
  • Introduction (historical view, scientific and economic relevance, scaling laws)
  • Semiconductor Technology Basics, Lithography (wafer fabrication, photolithography, improving resolution, next-generation lithography, nano-imprinting, molecular imprinting)
  • Deposition Techniques (thermal oxidation, epitaxy, electroplating, PVD techniques: evaporation and sputtering; CVD techniques: APCVD, LPCVD, PECVD and LECVD; screen printing)
  • Etching and Bulk Micromachining (definitions, wet chemical etching, isotropic etch with HNA, electrochemical etching, anisotropic etching with KOH/TMAH: theory, corner undercutting, measures for compensation and etch-stop techniques; plasma processes, dry etching: back sputtering, plasma etching, RIE, Bosch process, cryo process, XeF2 etching)
  • Surface Micromachining and alternative Techniques (sacrificial etching, film stress, stiction: theory and counter measures; Origami microstructures, Epi-Poly, porous silicon, SOI, SCREAM process, LIGA, SU8, rapid prototyping)
  • Thermal and Radiation Sensors (temperature measurement, self-generating sensors: Seebeck effect and thermopile; modulating sensors: thermo resistor, Pt-100, spreading resistance sensor, pn junction, NTC and PTC; thermal anemometer, mass flow sensor, photometry, radiometry, IR sensor: thermopile and bolometer)
  • Mechanical Sensors (strain based and stress based principle, capacitive readout, piezoresistivity,  pressure sensor: piezoresistive, capacitive and fabrication process; accelerometer: piezoresistive, piezoelectric and capacitive; angular rate sensor: operating principle and fabrication process)
  • Magnetic Sensors (galvanomagnetic sensors: spinning current Hall sensor and magneto-transistor; magnetoresistive sensors: magneto resistance, AMR and GMR, fluxgate magnetometer)
  • Chemical and Bio Sensors (thermal gas sensors: pellistor and thermal conductivity sensor; metal oxide semiconductor gas sensor, organic semiconductor gas sensor, Lambda probe, MOSFET gas sensor, pH-FET, SAW sensor, principle of biosensor, Clark electrode, enzyme electrode, DNA chip)
  • Micro Actuators, Microfluidics and TAS (drives: thermal, electrostatic, piezo electric and electromagnetic; light modulators, DMD, adaptive optics, microscanner, microvalves: passive and active, micropumps, valveless micropump, electrokinetic micropumps, micromixer, filter, inkjet printhead, microdispenser, microfluidic switching elements, microreactor, lab-on-a-chip, microanalytics)
  • MEMS in medical Engineering (wireless energy and data transmission, smart pill, implantable drug delivery system, stimulators: microelectrodes, cochlear and retinal implant; implantable pressure sensors, intelligent osteosynthesis, implant for spinal cord regeneration)
  • Design, Simulation, Test (development and design flows, bottom-up approach, top-down approach, testability, modelling: multiphysics, FEM and equivalent circuit simulation; reliability test, physics-of-failure, Arrhenius equation, bath-tub relationship)
  • System Integration (monolithic and hybrid integration, assembly and packaging, dicing, electrical contact: wire bonding, TAB and flip chip bonding; packages, chip-on-board, wafer-level-package, 3D integration, wafer bonding: anodic bonding and silicon fusion bonding; micro electroplating, 3D-MID)


Literature

M. Madou: Fundamentals of Microfabrication, CRC Press, 2002

N. Schwesinger: Lehrbuch Mikrosystemtechnik, Oldenbourg Verlag, 2009

T. M. Adams, R. A. Layton:Introductory MEMS, Springer, 2010

G. Gerlach; W. Dötzel: Introduction to microsystem technology, Wiley, 2008

Course L0725: Microsystems Technology
Typ Problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Hoc Khiem Trieu
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0792: Reserach Project in Medical Technology

Courses
Title Typ Hrs/wk CP
Module Responsible Dozenten des SD E
Admission Requirements None
Recommended Previous Knowledge

Advanced state of knowledge in the electrical engineering master program


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students know current research topics oft institutes engaged in their specialization. They can name the fundamental scientific methods used for doing related reserach.


Skills

Students are capable of completing a small, independent sub-project of currently ongoing research projects in the institutes engaged in their specialization. Students can justify and explain their approach for problem solving, they can draw conclusions from their results, and then can find new ways and methods for their work. Students are capable of comparing and assessing alterantive approaches with their own with regard to given criteria.


Personal Competence
Social Competence

Students are able to discuss their work progress with research assistants of the supervising institute .  They are capable of presenting their results in front of a professional audience.


Autonomy

Based on their competences gained so far students are capable of defining meaningful tasks within ongoing research project for themselves. They are able to develop the necessary understanding  and problem solving methods.


Workload in Hours Independent Study Time 180, Study Time in Lecture 0
Credit points 6
Examination Project (accord. to Subject Specific Regulations)
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Medical Technology: Elective Compulsory

Module M0921: Electronic Circuits for Medical Applications

Courses
Title Typ Hrs/wk CP
Electronic Circuits for Medical Applications (L0696) Lecture 2 3
Electronic Circuits for Medical Applications (L1056) Recitation Section (small) 1 2
Electronic Circuits for Medical Applications (L1408) Laboratory Course 1 1
Module Responsible NN
Admission Requirements None
Recommended Previous Knowledge Fundamentals of electrical engineering
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the basic functionality of the information transfer by the central nervous system
  • Students are able to explain the build-up of an action potential and its propagation along an axon
  • Students can exemplify the communication between neurons and electronic devices
  • Students can describe the special features of low-noise amplifiers for medical applications
  • Students can explain the functions of prostheses, e. g. an artificial hand
  • Students are able to discuss the potential and limitations of cochlea implants and artificial eyes


Skills
  • Students can  calculate the  time dependent voltage behavior of an action potential
  • Students can give scenarios for further improvement of low-noise and low-power signal acquisition.
  • Students  can develop the block diagrams of prosthetic systems
  • Students can define the building blocks of electronic systems for an articifial eye.


Personal Competence
Social Competence
  • Students are trained to solve problems in the field of medical electronics in teams together with experts with different professional background.
  • Students are able to recognize their specific limitations, so that they can ask for assistance to the right time.
  • Students can document their work in a clear manner and communicate their results in a way that others can be involved whenever it is necessary


Autonomy
  • Students are able to realistically judge the status of their knowledge and to define actions for improvements when necessary.
  • Students can break down their work in appropriate work packages and schedule their work in a realistic way.
  • Students can handle the complex data structures of bioelectrical experiments without needing support.
  • Students are able to act in a responsible manner in all cases and situations of experimental work.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 40 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Microelectronics and Microsystems: Specialisation Microelectronics Complements: Elective Compulsory
Course L0696: Electronic Circuits for Medical Applications
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer NN
Language EN
Cycle WiSe
Content
  • Market for medical instruments
  • Membrane potential, action potential, sodium-potassium pump
  • Information transfer by the central nervous system
  • Interface tissue - electrode
  • Amplifiers for medical applications, analog-digital converters
  • Examples for electronic implants
  • Artificial eye, cochlea implant



Literature

Kim E. Barret, Susan M. Barman, Scott Boitano and Heddwen L. Brooks

Ganong‘s Review of Medical Physiology, 24nd Edition, McGraw Hill Lange, 2010

Tier- und Humanphysiologie: Eine Einführung von Werner A. Müller (Author), Stephan Frings (Author), 657 p.,  4. editions, Springer, 2009

Robert F. Schmidt (Editor), Hans-Georg Schaible (Editor)

Neuro- und Sinnesphysiologie (Springer-Lehrbuch) (Paper back), 488 p., Springer, 2006, 5. Edition, currently online only
Russell K. Hobbie, Bradley J. Roth, Intermediate Physics for Medicine and Biology, Springer, 4th ed., 616 p., 2007

Vorlesungen der Universität Heidelberg zur Tier- und Humanphysiologie: http://www.sinnesphysiologie.de/gruvo03/gruvoin.htm

Internet: http://butler.cc.tut.fi/~malmivuo/bem/bembook/


Course L1056: Electronic Circuits for Medical Applications
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer NN
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L1408: Electronic Circuits for Medical Applications
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer NN
Language EN
Cycle WiSe
Content
  • Market for medical instruments
  • Membrane potential, action potential, sodium-potassium pump
  • Information transfer by the central nervous system
  • Interface tissue - electrode
  • Amplifiers for medical applications, analog-digital converters
  • Examples for electronic implants
  • Artificial eye, cochlea implant
Literature

Kim E. Barret, Susan M. Barman, Scott Boitano and Heddwen L. Brooks

Ganong‘s Review of Medical Physiology, 24nd Edition, McGraw Hill Lange, 2010

Tier- und Humanphysiologie: Eine Einführung von Werner A. Müller (Author), Stephan Frings (Author), 657 p.,  4. editions, Springer, 2009

Robert F. Schmidt (Editor), Hans-Georg Schaible (Editor)

Neuro- und Sinnesphysiologie (Springer-Lehrbuch) (Paper back), 488 p., Springer, 2006, 5. Edition, currently online only
Russell K. Hobbie, Bradley J. Roth, Intermediate Physics for Medicine and Biology, Springer, 4th ed., 616 p., 2007

Vorlesungen der Universität Heidelberg zur Tier- und Humanphysiologie: http://www.sinnesphysiologie.de/gruvo03/gruvoin.htm

Internet: http://butler.cc.tut.fi/~malmivuo/bem/bembook/

Module M1249: Numerical Methods for Medical Imaging

Courses
Title Typ Hrs/wk CP
Numerical Methods for Medical Imaging (L1694) Lecture 2 3
Numerical Methods for Medical Imaging (L1695) Recitation Section (small) 2 3
Module Responsible Prof. Tobias Knopp
Admission Requirements None
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Course L1694: Numerical Methods for Medical Imaging
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language DE
Cycle WiSe
Content
Literature

Bildgebende Verfahren in der Medizin; O. Dössel; Springer, Berlin, 2000

Bildgebende Systeme für die medizinische Diagnostik; H. Morneburg (Hrsg.); Publicis MCD, München, 1995

Introduction to the Mathematics of Medical Imaging; C. L.Epstein; Siam, Philadelphia, 2008

Medical Image Processing, Reconstruction and Restoration; J. Jan; Taylor and Francis, Boca Raton, 2006

Principles of Magnetic Resonance Imaging; Z.-P. Liang and P. C. Lauterbur; IEEE Press, New York, 1999

Course L1695: Numerical Methods for Medical Imaging
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1279: MED II: Introduction to Biochemistry and Molecular Biology

Courses
Title Typ Hrs/wk CP
Introduction to Biochemistry and Molecular Biology (L0386) Lecture 2 3
Module Responsible Prof. Hans-Jürgen Kreienkamp
Admission Requirements None
Recommended Previous Knowledge None
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students can
  • describe basic biomolecules;
  • explain how genetic information is coded in the DNA;
  • explain the connection between DNA and proteins;
Skills The students can
  • recognize the importance of molecular parameters for the course of a disease;
  • describe selected molecular-diagnostic procedures;
  • explain the relevance of these procedures for some diseases
Personal Competence
Social Competence

The students can participate in discussions in research and medicine on a technical level.

Autonomy

The students can develop understanding of topics from the course, using technical literature, by themselves.

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Examination Written exam
Examination duration and scale 60 minutes
Assignment for the Following Curricula General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory
General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory
Mechanical Engineering: Specialisation Biomechanics: Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Technomathematics: Core qualification: Elective Compulsory
Technomathematics: Specialisation III. Engineering Science: Elective Compulsory
Course L0386: Introduction to Biochemistry and Molecular Biology
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Hans-Jürgen Kreienkamp
Language DE
Cycle WiSe
Content
Literature

Müller-Esterl, Biochemie, Spektrum Verlag, 2010; 2. Auflage

Löffler, Basiswissen Biochemie, 7. Auflage, Springer, 2008




Specialization Modeling and Simulation


In this specialization students have the opportunity to select courses that focus on the areas of mathematical modeling, numerical techniques, computer aided engineering (CAE) and state-of- the-art simulation tools with application in electrical engineering. Students will learn to derive, implement, validate, and optimize numerical algorithms. Thereby students will obtain unique competencies at the interface between mathematics, computer science, and electrical engineering that are required for corresponding positions in industry and academia.

Module M0747: Microsystem Design

Courses
Title Typ Hrs/wk CP
Microsystem Design (L0683) Lecture 2 3
Microsystem Design (L0684) Laboratory Course 3 3
Module Responsible Prof. Manfred Kasper
Admission Requirements
Recommended Previous Knowledge

Mathematical Calculus, Linear Algebra, Microsystem Engineering

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students know about the most important and most common simulation and design methods used in microsystem design. The scientific background of finite element methods and the basic theory of these methods are known.

Skills

Students are able to apply simulation methods and commercial simulators in a goal oriented approach to complex design tasks. Students know to apply the theory in order achieve estimates of expected accuracy and can judge and verify the correctness of results. Students are able to develop a design approach even if only incomplete information about material data or constraints are available. Student can make use of approximate and reduced order models in a preliminary design stage or a system simulation.

Personal Competence
Social Competence

Students are able to solve specific problems alone or in a group and to present the results accordingly. Students can develop and explain their solution approach and subdivide the design task to subproblems which are solved separately by group members.

Autonomy

Students are able to acquire particular knowledge using specialized literature and to integrate and associate this knowledge with other fields.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Oral exam
Examination duration and scale halbstündig
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0683: Microsystem Design
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Manfred Kasper
Language EN
Cycle SoSe
Content

Finite difference methods

Approximation error

Finite element method

Order of convergence

Error estimation, mesh refinement

Makromodeling

Reduced order modeling

Black-box models

System identification

Multi-physics systems

System simulation

Levels of simulation, network simulation

Transient problems

Non-linear problems

Introduction to Comsol

Application to thermal, electric, electromagnetic, mechanical and fluidic problems

Literature

M. Kasper: Mikrosystementwurf, Springer (2000)

S. Senturia: Microsystem Design, Kluwer (2001)

Course L0684: Microsystem Design
Typ Laboratory Course
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Manfred Kasper
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0714: Numerical Treatment of Ordinary Differential Equations

Courses
Title Typ Hrs/wk CP
Numerical Treatment of Ordinary Differential Equations (L0576) Lecture 2 3
Numerical Treatment of Ordinary Differential Equations (L0582) Recitation Section (small) 2 3
Module Responsible Prof. Blanca Ayuso Dios
Admission Requirements None
Recommended Previous Knowledge
  • Mathematik I, II, III für Ingenieurstudierende (deutsch oder englisch) oder Analysis & Lineare Algebra I + II sowie Analysis III für Technomathematiker
  • Basic MATLAB knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • list numerical methods for the solution of ordinary differential equations and explain their core ideas,
  • repeat convergence statements for the treated numerical methods (including the prerequisites tied to the underlying problem),
  • explain aspects regarding the practical execution of a method.
Skills

Students are able to

  • implement (MATLAB), apply and compare numerical methods for the solution of ordinary differential equations,
  • to justify the convergence behaviour of numerical methods with respect to the posed problem and selected algorithm,
  • for a given problem, develop a suitable solution approach, if necessary by the composition of several algorithms, to execute this approach and to critically evaluate the results.


Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 180 min
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation General Process Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Energy Systems: Core qualification: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Compulsory
Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Course L0576: Numerical Treatment of Ordinary Differential Equations
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Patricio Farrell
Language DE/EN
Cycle SoSe
Content

Numerical methods for Initial Value Problems

  • single step methods
  • multistep methods
  • stiff problems
  • differential algebraic equations (DAE) of index 1

Numerical methods for Boundary Value Problems

  • initial value methods
  • multiple shooting method
  • difference methods
  • variational methods


Literature
  • E. Hairer, S. Noersett, G. Wanner: Solving Ordinary Differential Equations I: Nonstiff Problems
  • E. Hairer, G. Wanner: Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems
Course L0582: Numerical Treatment of Ordinary Differential Equations
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Patricio Farrell
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0692: Approximation and Stability

Courses
Title Typ Hrs/wk CP
Approximation and Stability (L0487) Lecture 2 3
Approximation and Stability (L0489) Seminar 1 2
Approximation and Stability (L0488) Recitation Section (small) 1 1
Module Responsible Prof. Marko Lindner
Admission Requirements None
Recommended Previous Knowledge
  • Linear Algebra: systems of linear equations, least squares problems, eigenvalues, singular values
  • Analysis: sequences, series, differentiation, integration
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • sketch and interrelate basic concepts of functional analysis (Hilbert space, operators),
  • name and understand concrete approximation methods,
  • name and explain basic stability theorems,
  • discuss spectral quantities, conditions numbers and methods of regularisation

Skills

Students are able to

  • apply basic results from functional analysis,
  • apply approximation methods,
  • apply stability theorems,
  • compute spectral quantities,
  • apply regularisation methods.
Personal Competence
Social Competence

Students are able to solve specific problems in groups and to present their results appropriately (e.g. as a seminar presentation).

Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0487: Approximation and Stability
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle SoSe
Content

This course is about solving the following basic problems of Linear Algebra,

  • systems of linear equations,
  • least squares problems,
  • eigenvalue problems

but now in function spaces (i.e. vector spaces of infinite dimension) by a stable approximation of the problem in a space of finite dimension.

Contents:

  • crash course on Hilbert spaces: metric, norm, scalar product, completeness
  • crash course on operators: boundedness, norm, compactness, projections
  • uniform vs. strong convergence, approximation methods
  • applicability and stability of approximation methods, Polski's theorem
  • Galerkin methods, collocation, spline interpolation, truncation
  • convolution and Toeplitz operators
  • crash course on C*-algebras
  • convergence of condition numbers
  • convergence of spectral quantities: spectrum, eigen values, singular values, pseudospectra
  • regularisation methods (truncated SVD, Tichonov)
Literature
  • R. Hagen, S. Roch, B. Silbermann: C*-Algebras in Numerical Analysis
  • H. W. Alt: Lineare Funktionalanalysis
  • M. Lindner: Infinite matrices and their finite sections
Course L0489: Approximation and Stability
Typ Seminar
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L0488: Approximation and Stability
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0653: High-Performance Computing

Courses
Title Typ Hrs/wk CP
Fundamentals of High-Performance Computing (L0242) Lecture 2 3
Fundamentals of High-Performance Computing (L1416) Problem-based Learning 2 3
Module Responsible Prof. Thomas Rung
Admission Requirements None
Recommended Previous Knowledge
  • Basic knowledge in usage of modern IT environment
  • Programming skills
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to outline the fundamentals of numerical algorithms for high-performance computers by reference to modern hardware examples. Students can explain the relation between hard- and software aspects for the design of algorithms.

Skills Student can perform a critical assesment of the computational efficiency of simulation approaches. 
Personal Competence
Social Competence Students are able to develop and code algorithms in a team.
Autonomy


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 1.5h
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Naval Architecture and Ocean Engineering: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0242: Fundamentals of High-Performance Computing
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Thomas Rung
Language DE/EN
Cycle SoSe
Content

Fundamentals of modern hardware architectur, critical hard- & software aspects for efficient processing of exemplary algorithms, concepts for shared- and distributed-memory systems, implementations for accelerator hardware (GPGPUs)

Literature
Course L1416: Fundamentals of High-Performance Computing
Typ Problem-based Learning
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Thomas Rung
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0935: Microcontroller Circuits: Implementation in Hardware and Software

Courses
Title Typ Hrs/wk CP
Microcontroller Circuits: Implementation in Hardware and Software (L0087) Seminar 2 2
Module Responsible Prof. Siegfried Rump
Admission Requirements none.
Recommended Previous Knowledge lecture: Computer Architectures
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students can describe parts and operation of a common family of microcontrollers. They know details about operations of CPUs, and they can transfer algorithms to machine code.
Skills

The students can design and use electronic circuits (digital with some analogue parts). Furthermore they are able to implement solutions of some tasks by way of assembler programming on these circuits.

Personal Competence
Social Competence

Groups of two students work on special projects. The students have the skill to separate the project into smaller parts and to present the achieved results in an appropriate short talk.

Autonomy The student can use, select and estimate suitable sources, which are available from information technology companies. They apply those findings to their projects.
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Written elaboration
Examination duration and scale 15 minutes + disputation
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Course L0087: Microcontroller Circuits: Implementation in Hardware and Software
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe/SoSe
Content
Literature

Module M0800: Numerical Methods for Electromagnetic Field Computation

Courses
Title Typ Hrs/wk CP
Numerical Methods for Electromagnetic Field Computation (L0802) Lecture 2 3
Numerical Methods for Electromagnetic Field Computation (L0803) Recitation Section (large) 1 1
Module Responsible Dr. Heinz-Dietrich Brüns
Admission Requirements

None

Recommended Previous Knowledge Basic principles of electromagnetic field theory
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Numerical methods in numerical field computation  are of increasing importance in electrical engineering, for example in the are of antenna development or for analyzing electromagnetic compatibility problems (EMC). The underlying principles of the major techniques that are currently applied in practice are explained. It turns out that each method has its strengths and weaknesses in relation to specific applications. The students shall be enabled to evaluate which kind of method could be advantageous for a certain case and if an application concerning a certain problem area is manageable at all.

Skills

The students will be able to set up discretized models based on the working principle of the chosen numerical method. This is carried out regarding the electrical size and considering the geometrical complexity. The students know the  interrelationship between the number of grid elements (surface patches, cells), the necessary memory resulting form this and the computation time. They are aware of the requirements of the method under consideration to achieve convergent results and they learn to validate these results using various techniques. The students are able to distinguish between methods that are used in the time domain, in the frequency domain and in the range of electrostatics. Furthermore the students know the advantages, possibilities and constraints of surface and volume based techniques.

Personal Competence
Social Competence

In practical exercises small groups of students can apply the program system CONCEPT-II, which is based on one of the most important techniques, the so-called method of moments. The program is under continuous development at the Institute of Electromagnetic Theory.

Autonomy

The students are able to generally apply their new knowledge in electromagnetics and to associate it with other courses. On the basis of the introduction given in the lecture they are capable to easily learn more about a technique from the given literature.

Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Oral exam
Examination duration and scale 30 Minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Course L0802: Numerical Methods for Electromagnetic Field Computation
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle SoSe
Content

-Short and in details more comprehensive repetition of relevant fields of electromagnetic theory
-Introduction into the finite difference method with emphasis on electrostatics and into the charge simulation method
-Basics of the boundary element method in electrostatics
-Hygens principle, magnetic currents in numerics
-FDTD, FIT (finite integration technique) as important techniques for time domain applications
-Finite element method (FEM)
-The method of moments in the frequency domain
-TLM in the time domain
-Possibilities for validating numerical solutions
-Application of hybrid techniques in special problem areas

Literature

Allen Tavlove, Susan C. Hagness: Computational Electrodynamics: The Finite-Difference
Time-Domain Method, Artech House Inc., 2005

Walton C. Gibson: The Method of Moments in Electromagnetics, Chapman & Hall/CRC

Ianming Jin: The Finite Element Method in Electromagnetics, John Wiley & Sons, Inc.,
second edition, 2002

Pei-bai Zhou: Numerical Analysis of Electromagnetic Fields, Springer-Verlag, 1993

C. Christopoulos: The Transmission-Line Modeling (TLM) Method in Electromagnetics,
Morgan&Claypool Publishers, 2006

Course L0803: Numerical Methods for Electromagnetic Field Computation
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle SoSe
Content

-Short and in details more comprehensive repetition of relevant fields of electromagnetic theory
-Introduction into the finite difference method with emphasis on electrostatics and into the charge simulation method
-Basics of the boundary element method in electrostatics
-Hygens principle, magnetic currents in numerics
-FDTD, FIT (finite integration technique) as important techniques for time domain applications
-Finite element method (FEM)
-The method of moments in the frequency domain
-TLM in the time domain
-Possibilities for validating numerical solutions
-Application of hybrid techniques in special problem areas

Literature

Allen Tavlove, Susan C. Hagness: Computational Electrodynamics: The Finite-Difference
Time-Domain Method, Artech House Inc., 2005

Walton C. Gibson: The Method of Moments in Electromagnetics, Chapman & Hall/CRC

Ianming Jin: The Finite Element Method in Electromagnetics, John Wiley & Sons, Inc.,
second edition, 2002

Pei-bai Zhou: Numerical Analysis of Electromagnetic Fields, Springer-Verlag, 1993

C. Christopoulos: The Transmission-Line Modeling (TLM) Method in Electromagnetics,
Morgan&Claypool Publishers, 2006

Module M0715: Solvers for Sparse Linear Systems

Courses
Title Typ Hrs/wk CP
Solvers for Sparse Linear Systems (L0583) Lecture 2 3
Solvers for Sparse Linear Systems (L0584) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics I + II for Engineering students or Analysis & Lineare Algebra I + II for Technomathematicians
  • Programming experience in C
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can

  • list classical and modern iteration methods and their interrelationships,
  • repeat convergence statements for iteration methods,
  • explain aspects regarding the efficient implementation of iteration methods.
Skills

Students are able to

  • implement, test, and compare iterative methods,
  • analyse the convergence behaviour of iterative methods and, if applicable, compute congergence rates.
Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to work on complex problems over an extended period of time,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30 minutes
Assignment for the Following Curricula Computer Science: Specialisation Computational Mathematics: Elective Compulsory
Electrical Engineering: Core qualification: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Course L0583: Solvers for Sparse Linear Systems
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne
Language DE/EN
Cycle SoSe
Content
  1. Sparse systems: Orderings and storage formats, direct solvers
  2. Classical methods: basic notions, convergence
  3. Projection methods
  4. Krylov space methods
  5. Preconditioning (e.g. ILU)
  6. Multigrid methods
Literature
  1. Y. Saad, Iterative methods for sparse linear systems
Course L0584: Solvers for Sparse Linear Systems
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1316: Research Project in Modeling and Simulation

Courses
Title Typ Hrs/wk CP
Module Responsible Dozenten des SD E
Admission Requirements None
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 180, Study Time in Lecture 0
Credit points 6
Examination Project (accord. to Subject Specific Regulations)
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory

Module M1249: Numerical Methods for Medical Imaging

Courses
Title Typ Hrs/wk CP
Numerical Methods for Medical Imaging (L1694) Lecture 2 3
Numerical Methods for Medical Imaging (L1695) Recitation Section (small) 2 3
Module Responsible Prof. Tobias Knopp
Admission Requirements None
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Course L1694: Numerical Methods for Medical Imaging
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language DE
Cycle WiSe
Content
Literature

Bildgebende Verfahren in der Medizin; O. Dössel; Springer, Berlin, 2000

Bildgebende Systeme für die medizinische Diagnostik; H. Morneburg (Hrsg.); Publicis MCD, München, 1995

Introduction to the Mathematics of Medical Imaging; C. L.Epstein; Siam, Philadelphia, 2008

Medical Image Processing, Reconstruction and Restoration; J. Jan; Taylor and Francis, Boca Raton, 2006

Principles of Magnetic Resonance Imaging; Z.-P. Liang and P. C. Lauterbur; IEEE Press, New York, 1999

Course L1695: Numerical Methods for Medical Imaging
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Tobias Knopp
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0586: Efficient Algorithms

Courses
Title Typ Hrs/wk CP
Efficient Algorithms (L0120) Lecture 2 3
Efficient Algorithms (L1207) Recitation Section (small) 2 3
Module Responsible Prof. Siegfried Rump
Admission Requirements None
Recommended Previous Knowledge

Programming in Matlab and/or C

Basic knowledge in discrete mathematics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students are able to explain the basic theory and methods of network algorithms and in particular their data structures. They are able to analyze the computational behavior and computing time of linear programming algorithms as well network algorithms. Moreover the students can distinguish between efficiently solvable and NP-hard problems.

Skills

The students are able to analyze complex tasks and can determine possibilities to transform them into networking algorithms. In particular they can efficiently implement basic algorithms and data structures of LP- and network algorithms and identify possible weaknesses. They are able to distinguish between different efficient data structures and are able to use them appropriately.

Personal Competence
Social Competence

The students have the skills to solve problems together in small groups and to present the achieved results in an appropriate manner.

Autonomy

The students are able to retrieve necessary informations from the given literature and to combine them with the topics of the lecture. Throughout the lecture they can check their abilities and knowledge on the basis of given exercises and test questions providing an aid to optimize their learning process.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0120: Efficient Algorithms
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content

- Linear Programming

- Data structures

- Leftist heaps

- Minimum spanning tree

- Shortest path

- Maximum flow

- NP-hard problems via max-cut

Literature

R. E. Tarjan: Data Structures and Network Algorithms. CBMS 44, Society for Industrial and Applied Mathematics, Philadelphia, PA, 1983.

Wesley, 2011 http://algs4.cs.princeton.edu/home/

V. Chvátal, ``Linear Programming'', Freeman, New York, 1983.

Course L1207: Efficient Algorithms
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0881: Mathematical Image Processing

Courses
Title Typ Hrs/wk CP
Mathematical Image Processing (L0991) Lecture 3 4
Mathematical Image Processing (L0992) Recitation Section (small) 1 2
Module Responsible Prof. Marko Lindner
Admission Requirements None
Recommended Previous Knowledge
  • Analysis: partial derivatives, gradient, directional derivative
  • Linear Algebra: eigenvalues, least squares solution of a linear system
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to 

  • characterize and compare diffusion equations
  • explain elementary methods of image processing
  • explain methods of image segmentation and registration
  • sketch and interrelate basic concepts of functional analysis 
Skills

Students are able to 

  • implement and apply elementary methods of image processing  
  • explain and apply modern methods of image processing
Personal Competence
Social Competence

Students are able to work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge) and to explain theoretical foundations.

Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 20 min
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Course L0991: Mathematical Image Processing
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle WiSe
Content
  • basic methods of image processing
  • smoothing filters
  • the diffusion / heat equation
  • variational formulations in image processing
  • edge detection
  • image segmentation
  • image registration
Literature Bredies/Lorenz: Mathematische Bildverarbeitung
Course L0992: Mathematical Image Processing
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0716: Hierarchical Algorithms

Courses
Title Typ Hrs/wk CP
Hierarchical Algorithms (L0585) Lecture 2 3
Hierarchical Algorithms (L0586) Recitation Section (small) 2 3
Module Responsible Prof. Sabine Le Borne
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics I, II, III for Engineering students (german or english) or Analysis & Linear Algebra I + II as well as Analysis III for Technomathematicians
  • Programming experience in C
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • name representatives of hierarchical algorithms and list their characteristics,
  • explain construction techniques for hierarchical algorithms,
  • discuss aspects regarding the efficient implementation of hierarchical algorithms.
Skills

Students are able to

  • implement the hierarchical algorithms discussed in the lecture,
  • analyse the storage and computational complexities of the algorithms,
  • adapt algorithms to problem settings of various applications and thus develop problem adapted variants.
Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to work on complex problems over an extended period of time,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 20 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0585: Hierarchical Algorithms
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne
Language DE/EN
Cycle WiSe
Content
  • Low rank matrices
  • Separable expansions
  • Hierarchical matrix expansions
  • Hierarchical matrices
  • Formatted matrix operations
  • Applications
  • Additional topics
Literature W. Hackbusch: Hierarchische Matrizen: Algorithmen und Analysis
Course L0586: Hierarchical Algorithms
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Sabine Le Borne
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0720: Matrix Algorithms

Courses
Title Typ Hrs/wk CP
Matrix Algorithms (L0984) Lecture 2 3
Matrix Algorithms (L0985) Recitation Section (small) 2 3
Module Responsible Dr. Jens-Peter Zemke
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics I - III
  • Numerical Mathematics/ Numerics
  • Basic knowledge of the programming languages Matlab and C
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  1. name, state and classify state-of-the-art Krylov subspace  methods for the solution of the core problems of the engineering sciences, namely, eigenvalue problems, solution of linear systems, and model reduction;
  2. state approaches for the solution of matrix equations (Sylvester, Lyapunov, Riccati).
Skills

Students are capable to

  1. implement and assess basic Krylov subspace methods for the solution of eigenvalue problems, linear systems, and model reduction;
  2. assess methods used in modern software with respect to computing time, stability, and domain of applicability;
  3. adapt the approaches learned to new, unknown types of problem.
Personal Competence
Social Competence

Students can

  • develop and document joint solutions in small teams;
  • form groups to further develop the ideas and transfer them to other areas of applicability;
  • form a team to develop, build, and advance a software library.
Autonomy

Students are able to

  • correctly assess the time and effort of self-defined work;
  • assess whether the supporting theoretical and practical excercises are better solved individually or in a team;
  • define test problems for testing and expanding the methods;
  • assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0984: Matrix Algorithms
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Jens-Peter Zemke
Language DE
Cycle WiSe
Content
  • Part A: Krylov Subspace Methods:
    • Basics (derivation, basis, Ritz, OR, MR)
    • Arnoldi-based methods (Arnoldi, GMRes)
    • Lanczos-based methods (Lanczos, CG, BiCG, QMR, SymmLQ, PvL)
    • Sonneveld-based methods (IDR, BiCGStab, TFQMR, IDR(s))
  • Part B: Matrix Equations:
    • Sylvester Equation
    • Lyapunov Equation
    • Algebraic Riccati Equation
Literature Skript
Course L0985: Matrix Algorithms
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Jens-Peter Zemke
Language DE
Cycle WiSe
Content
Literature Siehe korrespondierende Vorlesung

Specialization Information and Communication Systems


This specialization offers a wide range of topics with respect to various concepts of telecommunications, wireless and wired communication systems as well as methods of digital signal processing. Students are able to understand the characteristics of transmission channels and principles of wireless systems in detail. Moreover, they acquire a profound knowledge about fundamentals, structures and modelling of communication networks. In addition, know-how on digital speech, audio and image processing is provided. As a result, the students will have the skills to analyze, design and optimize all aspects of a communication system. In today’s information age, this expertise is of paramount importance for positions in industry and academia.

Module M0551: Pattern Recognition and Data Compression

Courses
Title Typ Hrs/wk CP
Pattern Recognition and Data Compression (L0128) Lecture 4 6
Module Responsible Prof. Rolf-Rainer Grigat
Admission Requirements
Recommended Previous Knowledge

Linear algebra (including PCA, unitary transforms), stochastics and statistics, binary arithmetics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can name the basic concepts of pattern recognition and data compression.

Students are able to discuss logical connections between the concepts covered in the course and to explain them by means of examples.


Skills

Students can apply statistical methods to classification problems in pattern recognition and to prediction in data compression. On a sound theoretical and methodical basis they can analyze characteristic value assignments and classifications and describe data compression and video signal coding. They are able to use highly sophisticated methods and processes of the subject area. Students are capable of assessing different solution approaches in multidimensional decision-making areas.



Personal Competence
Social Competence
Autonomy

Students are capable of identifying problems independently and of solving them scientifically, using the methods they have learnt.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 60 Minutes, Content of Lecture and materials in StudIP
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0128: Pattern Recognition and Data Compression
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Rolf-Rainer Grigat
Language EN
Cycle SoSe
Content

Structure of a pattern recognition system, statistical decision theory, classification based on statistical models, polynomial regression, dimension reduction, multilayer perceptron regression, radial basis functions, support vector machines, unsupervised learning and clustering, algorithm-independent machine learning, mixture models and EM, adaptive basis function models and boosting, Markov random fields

Information, entropy, redundancy, mutual information, Markov processes, basic coding schemes (code length, run length coding, prefix-free codes), entropy coding (Huffman, arithmetic coding), dictionary coding (LZ77/Deflate/LZMA2, LZ78/LZW), prediction, DPCM, CALIC, quantization (scalar and vector quantization), transform coding, prediction, decorrelation (DPCM, DCT, hybrid DCT, JPEG, JPEG-LS), motion estimation, subband coding, wavelets, HEVC (H.265,MPEG-H)

Literature

Schürmann: Pattern Classification, Wiley 1996
Murphy, Machine Learning, MIT Press, 2012
Barber, Bayesian Reasoning and Machine Learning, Cambridge, 2012
Duda, Hart, Stork: Pattern Classification, Wiley, 2001
Bishop: Pattern Recognition and Machine Learning, Springer 2006

Salomon, Data Compression, the Complete Reference, Springer, 2000
Sayood, Introduction to Data Compression, Morgan Kaufmann, 2006
Ohm, Multimedia Communication Technology, Springer, 2004
Solari, Digital video and audio compression, McGraw-Hill, 1997
Tekalp, Digital Video Processing, Prentice Hall, 1995

Module M0637: Advanced Concepts of Wireless Communications

Courses
Title Typ Hrs/wk CP
Advanced Concepts of Wireless Communications (L0297) Lecture 3 4
Advanced Concepts of Wireless Communications (L0298) Recitation Section (large) 1 2
Module Responsible Dr. Rainer Grünheid
Admission Requirements None
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 90 minutes; scope: content of lecture and exercise
Assignment for the Following Curricula Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Course L0297: Advanced Concepts of Wireless Communications
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Dr. Rainer Grünheid
Language EN
Cycle SoSe
Content

The lecture deals with technical principles and related concepts of mobile communications. In this context, the main focus is put on the physical and data link layer of the ISO-OSI stack.

In the lecture, the transmission medium, i.e., the mobile radio channel, serves as the starting point of all considerations. The characteristics and the mathematical descriptions of the radio channel are discussed in detail. Subsequently, various physical layer aspects of wireless transmission are covered, such as channel coding, modulation/demodulation, channel estimation, synchronization, and equalization. Moreover, the different uses of multiple antennas at the transmitter and receiver, known as MIMO techniques, are described. Besides these physical layer topics, concepts of multiple access schemes in a cellular network are outlined.

In order to illustrate the above-mentioned technical solutions, the lecture will also provide a system view, highlighting the basics of some contemporary wireless systems, including UMTS/HSPA, LTE, LTE Advanced, and WiMAX.


Literature

John G. Proakis, Masoud Salehi: Digital Communications. 5th Edition, Irwin/McGraw Hill, 2007

David Tse, Pramod Viswanath: Fundamentals of Wireless Communication. Cambridge, 2005

Bernard Sklar: Digital Communications: Fundamentals and Applications. 2nd Edition, Pearson, 2013

Stefani Sesia, Issam Toufik, Matthew Baker: LTE - The UMTS Long Term Evolution. Second Edition, Wiley, 2011

Course L0298: Advanced Concepts of Wireless Communications
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dr. Rainer Grünheid
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0837: Communication Networks II - Simulation and Modeling

Courses
Title Typ Hrs/wk CP
Simulation and Modelling of Communication Networks (L0887) Problem-based Learning 5 6
Module Responsible Prof. Andreas Timm-Giel
Admission Requirements None
Recommended Previous Knowledge
  • Knowledge of computer and communication networks
  • Basic programming skills
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain the necessary stochastics, the discrete event simulation technology and modelling of networks for performance evaluation.

Skills

Students are able to apply the method of simulation for performance evaluation to different, also not practiced, problems of communication networks. The students can analyse the obtained results and explain the effects observed in the network. They are able to question their own results.

Personal Competence
Social Competence

Students are able to acquire expert knowledge in groups, present the results, and discuss solution approaches and results. They are able to work out solutions for new problems in small teams.

Autonomy

Students are able to transfer independently and in discussion with others the acquired method and expert knowledge to new problems. They can identify missing knowledge and acquire this knowledge independently.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Colloquium
Examination duration and scale 45-60 minutes colloquium with two students, therefore about 30 minutes per student.
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory
Course L0887: Simulation and Modelling of Communication Networks
Typ Problem-based Learning
Hrs/wk 5
CP 6
Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle SoSe
Content

In the course necessary basic stochastics and the discrete event simulation are introduced. Also simulation models for communication networks, for example, traffic models, mobility models and radio channel models are presented in the lecture. Students work with a simulation tool, where they can directly try out the acquired skills, algorithms and models. At the end of the course increasingly complex networks and protocols are considered and their performance is determined by simulation.

Literature
  • Skript des Instituts für Kommunikationsnetze

Further literature is announced at the beginning of the lecture.

Module M1318: Wireless Sensor Networks

Courses
Title Typ Hrs/wk CP
Selected Topics of Wireless Sensor Networks (L1819) Problem-based Learning 1 2
Wireless Sensor Networks (L1815) Lecture 2 2
Wireless Sensor Networks (L1816) Recitation Section (small) 1 2
Module Responsible Prof. Bernd-Christian Renner
Admission Requirements None
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Course L1819: Selected Topics of Wireless Sensor Networks
Typ Problem-based Learning
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Bernd-Christian Renner
Language EN
Cycle SoSe
Content

Selected topics on sensor network research will be researched in a PBL course by the students in groups and will be presented in a poster session at the end of the term. Topics are:

  • Energy-efficient / low-power Medium Access
  • Energy-efficient / low-power Routing (Data Collection and Data Dissemination)
  • Energy Harvesting
  • Intermittently Powered Sensor Nodes
  • Energy-Aware Load Adaptation and Scheduling
  • Additional Topics will be provided on demand / depending on the number of participants
Literature

Will be provided individually

Course L1815: Wireless Sensor Networks
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Bernd-Christian Renner
Language EN
Cycle SoSe
Content
Literature
Course L1816: Wireless Sensor Networks
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Bernd-Christian Renner
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0673: Information Theory and Coding

Courses
Title Typ Hrs/wk CP
Information Theory and Coding (L0436) Lecture 3 4
Information Theory and Coding (L0438) Recitation Section (large) 1 2
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics 1-3
  • Probability theory and random processes
  • Basic knowledge of communications engineering (e.g. from lecture "Fundamentals of Communications and Random Processes")
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know the basic definitions for quantification of information in the sense of information theory. They know Shannon's source coding theorem and channel coding theorem and are able to determine theoretical limits of data compression and error-free data transmission over noisy channels. They understand the principles of source coding as well as error-detecting and error-correcting channel coding. They are familiar with the principles of decoding, in particular with modern methods of iterative decoding. They know fundamental coding schemes, their properties and decoding algorithms. 
Skills The students are able to determine the limits of data compression as well as of data transmission through noisy channels and based on those limits to design basic parameters of a transmission scheme. They can estimate the parameters of an error-detecting or error-correcting channel coding scheme for achieving certain performance targets. They are able to compare the properties of basic channel coding and decoding schemes regarding error correction capabilities, decoding delay, decoding complexity and to decide for a suitable method. They are capable of implementing basic coding and decoding schemes in software.
Personal Competence
Social Competence

The students can jointly solve specific problems.

Autonomy

The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Information and Communication Systems: Core qualification: Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Course L0436: Information Theory and Coding
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle SoSe
Content
  • Fundamentals of information theory

    • Self information, entropy, mutual information

    • Source coding theorem, channel coding theorem

    • Channel capacity of various channels

  • Fundamental source coding algorithms:

    • Huffman Code, Lempel Ziv Algorithm

  • Fundamentals of channel coding

    • Basic parameters of channel coding and respective bounds

    • Decoding principles: Maximum-A-Posteriori Decoding, Maximum-Likelihood Decoding, Hard-Decision-Decoding and Soft-Decision-Decoding

    • Error probability

  • Block codes

  • Low Density Parity Check (LDPC) Codes and iterative Ddecoding

  • Convolutional codes and Viterbi-Decoding

  • Turbo Codes and iterative decoding

  • Coded Modulation

Literature

Bossert, M.: Kanalcodierung. Oldenbourg.

Friedrichs, B.: Kanalcodierung. Springer.

Lin, S., Costello, D.: Error Control Coding. Prentice Hall.

Roth, R.: Introduction to Coding Theory.

Johnson, S.: Iterative Error Correction. Cambridge.

Richardson, T., Urbanke, R.: Modern Coding Theory. Cambridge University Press.

Gallager, R. G.: Information theory and reliable communication. Whiley-VCH

Cover, T., Thomas, J.: Elements of information theory. Wiley.

Course L0438: Information Theory and Coding
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0678: Seminar Communications Engineering

Courses
Title Typ Hrs/wk CP
Seminar Communications Engineering (L0448) Seminar 2 2
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge

One or more of the following moduls:

  • Digital Communications
  • Mobile Communications
  • Information theory and coding
  • Modern Wireless Systems
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students prepare on their own a special topic from communications engineering or digital signal processing.
Skills The students are able to prepare on their own a special topic from communications engineering or digital signal processing and present it in a seminar talk. They are able to discuss about the topic in a wider context. Furthermore, they are able to contribute to the discussion of other presentations during the seminar.
Personal Competence
Social Competence The students are able to discuss within the semnar group.
Autonomy
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Presentation
Examination duration and scale 30 minutes presentation, related material, active discussion
Assignment for the Following Curricula Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0448: Seminar Communications Engineering
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Gerhard Bauch
Language DE/EN
Cycle WiSe/SoSe
Content changing topics
Literature  je nach Thema

Module M1248: Compilers for Embedded Systems

Courses
Title Typ Hrs/wk CP
Compilers for Embedded Systems (L1692) Lecture 3 4
Compilers for Embedded Systems (L1693) Laboratory 1 2
Module Responsible Prof. Heiko Falk
Admission Requirements None
Recommended Previous Knowledge

Module "Embedded Systems"

C/C++ Programming skills

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The relevance of embedded systems increases from year to year. Within such systems, the amount of software to be executed on embedded processors grows continuously due to its lower costs and higher flexibility. Because of the particular application areas of embedded systems, highly optimized and application-specific processors are deployed. Such highly specialized processors impose high demands on compilers which have to generate code of highest quality. After the successful attendance of this course, the students are able

  • to illustrate the structure and organization of such compilers,
  • to distinguish and explain intermediate representations of various abstraction levels, and
  • to assess optimizations and their underlying problems in all compiler phases.

The high demands on compilers for embedded systems make effective code optimizations mandatory. The students learn in particular,

  • which kinds of optimizations are applicable at the source code level,
  • how the translation from source code to assembly code is performed,
  • which kinds of optimizations are applicable at the assembly code level,
  • how register allocation is performed, and
  • how memory hierarchies can be exploited effectively.

Since compilers for embedded systems often have to optimize for multiple objectives (e.g., average- or worst-case execution time, energy dissipation, code size), the students learn to evaluate the influence of optimizations on these different criteria.

Skills

After successful completion of the course, students shall be able to translate high-level program code into machine code. They will be enabled to assess which kind of code optimization should be applied most effectively at which abstraction level (e.g., source or assembly code) within a compiler.

While attending the labs, the students will learn to implement a fully functional compiler including optimizations.

Personal Competence
Social Competence

Students are able to solve similar problems alone or in a group and to present the results accordingly.

Autonomy

Students are able to acquire new knowledge from specific literature and to associate this knowledge with other classes.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30 minutes, contents of course
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Course L1692: Compilers for Embedded Systems
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Heiko Falk
Language DE/EN
Cycle SoSe
Content
  • Introduction and Motivation
  • Compilers for Embedded Systems - Requirements and Dependencies
  • Internal Structure of Compilers
  • Pre-Pass Optimizations
  • HIR Optimizations and Transformations
  • Code Generation
  • LIR Optimizations and Transformations
  • Register Allocation
  • WCET-Aware Compilation
  • Outlook
Literature
  • Peter Marwedel. Embedded System Design - Embedded Systems Foundations of Cyber-Physical Systems. 2nd Edition, Springer, 2012.
  • Steven S. Muchnick. Advanced Compiler Design and Implementation. Morgan Kaufmann, 1997.
  • Andrew W. Appel. Modern compiler implementation in C. Oxford University Press, 1998.
Course L1693: Compilers for Embedded Systems
Typ Laboratory
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Heiko Falk
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0550: Digital Image Analysis

Courses
Title Typ Hrs/wk CP
Digital Image Analysis (L0126) Lecture 4 6
Module Responsible Prof. Rolf-Rainer Grigat
Admission Requirements None
Recommended Previous Knowledge

System theory of one-dimensional signals (convolution and correlation, sampling theory, interpolation and decimation, Fourier transform, linear time-invariant systems), linear algebra (Eigenvalue decomposition, SVD), basic stochastics and statistics (expectation values, influence of sample size, correlation and covariance, normal distribution and its parameters), basics of Matlab, basics in optics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can

  • Describe imaging processes
  • Depict the physics of sensorics
  • Explain linear and non-linear filtering of signals
  • Establish interdisciplinary connections in the subject area and arrange them in their context
  • Interpret effects of the most important classes of imaging sensors and displays using mathematical methods and physical models.


Skills

Students are able to

  • Use highly sophisticated methods and procedures of the subject area
  • Identify problems and develop and implement creative solutions.

Students can solve simple arithmetical problems relating to the specification and design of image processing and image analysis systems.

Students are able to assess different solution approaches in multidimensional decision-making areas.

Students can undertake a prototypical analysis of processes in Matlab.


Personal Competence
Social Competence k.A.


Autonomy

Students can solve image analysis tasks independently using the relevant literature.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 60 Minutes, Content of Lecture and materials in StudIP
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Course L0126: Digital Image Analysis
Typ Lecture
Hrs/wk 4
CP 6
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Lecturer Prof. Rolf-Rainer Grigat
Language EN
Cycle WiSe
Content
  • Image representation, definition of images and volume data sets, illumination, radiometry, multispectral imaging, reflectivities, shape from shading
  • Perception of luminance and color, color spaces and transforms, color matching functions, human visual system, color appearance models
  • imaging sensors (CMOS, CCD, HDR, X-ray, IR), sensor characterization(EMVA1288), lenses and optics
  • spatio-temporal sampling (interpolation, decimation, aliasing, leakage, moiré, flicker, apertures)
  • features (filters, edge detection, morphology, invariance, statistical features, texture)
  • optical flow ( variational methods, quadratic optimization, Euler-Lagrange equations)
  • segmentation (distance, region growing, cluster analysis, active contours, level sets, energy minimization and graph cuts)
  • registration (distance and similarity, variational calculus, iterative closest points)
Literature

Bredies/Lorenz, Mathematische Bildverarbeitung, Vieweg, 2011
Wedel/Cremers, Stereo Scene Flow for 3D Motion Analysis, Springer 2011
Handels, Medizinische Bildverarbeitung, Vieweg, 2000
Pratt, Digital Image Processing, Wiley, 2001
Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1989

Module M0796: Research Project in Information and Communication Systems

Courses
Title Typ Hrs/wk CP
Module Responsible Dozenten des SD E
Admission Requirements None
Recommended Previous Knowledge

Advanced state of knowledge in the electrical engineering master program


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students know current research topics oft institutes engaged in their specialization. They can name the fundamental scientific methods used for doing related reserach.


Skills

Students are capable of completing a small, independent sub-project of currently ongoing research projects in the institutes engaged in their specialization. Students can justify and explain their approach for problem solving, they can draw conclusions from their results, and then can find new ways and methods for their work. Students are capable of comparing and assessing alterantive approaches with their own with regard to given criteria.


Personal Competence
Social Competence

Students are able to discuss their work progress with research assistants of the supervising institute .  They are capable of presenting their results in front of a professional audience.


Autonomy

Based on their competences gained so far students are capable of defining meaningful tasks within ongoing research project for themselves. They are able to develop the necessary understanding  and problem solving methods.


Workload in Hours Independent Study Time 180, Study Time in Lecture 0
Credit points 6
Examination Project (accord. to Subject Specific Regulations)
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory

Module M0638: Modern Wireless Systems

Courses
Title Typ Hrs/wk CP
Modern Wireless Systems (L0296) Lecture 2 3
Module Responsible Dr. Rainer Grünheid
Admission Requirements None
Recommended Previous Knowledge
  • Lecture "Digital Communications"
  • Lecture "Advanced Concepts of Wireless Communications"
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students have an overview of a variety of contemporary wireless systems of different size and complexity. They understand the technical solutions from the perspective of the physical and data link layer. They have developed a system view and are aware of the technical arguments, considering the respective applications and associated constraints. For several examples (e.g., Long Term Evolution, LTE), students are able to explain different concepts in a very deep technical detail.
Skills Students have developed a system view. They can transfer their knowledge to evaluate other systems, not discussed in the lecture, and to understand the respective technical solutions. Given specific contraints and technical requirements, students are in a position to make proposals for certain design aspects by an appropriate assessment and the consideration of alternatives.
Personal Competence
Social Competence

Students can jointly elaborate tasks in small groups and present their results in an adequate fashion.

Autonomy

Students are able to extract necessary information from given literature sources and put it into the perspective of the lecture. They can continuously check their level of expertise with the help of accompanying measures (such as online tests, clicker questions, exercise tasks) and, based on that, to steer their learning process accordingly. They can relate their acquired knowledge to topics of other lectures, e.g., "Digital Communications" and "Advanced Topics of Wireless Communications".

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Examination Oral exam
Examination duration and scale 40 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Course L0296: Modern Wireless Systems
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Rainer Grünheid
Language EN
Cycle WiSe
Content

The lecture gives an overview of contemporary wireless communication concepts and related techniques from a system point of view. For that purpose, different systems, ranging from Wireless Personal to Wide Area Networks, are covered, mainly discussing the physical and data link layer.

Systems under consideration include:
- ZigBee / IEEE 802.15.4
- Bluetooth
- IEEE 802.11 family
- Long Term Evolution (LTE) and LTE Advanced
- WiMAX

A special focus is placed on 4th generation networks; in particular, an in-depth view into the technical principles of the Long Term Evolution (LTE / LTE Advanced ) standard is given, with an emphasis on multiple antenna techniques.

Literature

John G. Proakis, Masoud Salehi: Digital Communications. 5th Edition, Irwin/McGraw Hill, 2007

Stefani Sesia, Issam Toufik, Matthew Baker: LTE - The UMTS Long Term Evolution. Second Edition, Wiley, 2011

Jeffrey G. Andrews, Arunabha Ghosh, Rias Muhamed: Fundamentals of WiMAX. Prentice Hall, 2007


Module M0836: Communication Networks I - Analysis and Structure

Courses
Title Typ Hrs/wk CP
Analysis and Structure of Communication Networks (L0897) Lecture 2 2
Selected Topics of Communication Networks (L0899) Problem-based Learning 2 2
Communication Networks Excercise (L0898) Problem-based Learning 1 2
Module Responsible Prof. Andreas Timm-Giel
Admission Requirements None
Recommended Previous Knowledge
  • Fundamental stochastics
  • Basic understanding of computer networks and/or communication technologies is beneficial
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to describe the principles and structures of communication networks in detail. They can explain the formal description methods of communication networks and their protocols. They are able to explain how current and complex communication networks work and describe the current research in these examples.

Skills

Students are able to evaluate the performance of communication networks using the learned methods. They are able to work out problems themselves and apply the learned methods. They can apply what they have learned autonomously on further and new communication networks.

Personal Competence
Social Competence

Students are able to define tasks themselves in small teams and solve these problems together using the learned methods. They can present the obtained results. They are able to discuss and critically analyse the solutions.

Autonomy

Students are able to obtain the necessary expert knowledge for understanding the functionality and performance capabilities of new communication networks independently.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Colloquium
Examination duration and scale 1.5 hours colloquium with three students, therefore about 30 min per student. Topics of the colloquium are the posters from the previous poster session and the topics of the module.
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Course L0897: Analysis and Structure of Communication Networks
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle WiSe
Content
Literature
  • Skript des Instituts für Kommunikationsnetze
  • Tannenbaum, Computernetzwerke, Pearson-Studium


Further literature is announced at the beginning of the lecture.

Course L0899: Selected Topics of Communication Networks
Typ Problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dr. Maciej Mühleisen
Language EN
Cycle WiSe
Content Example networks selected by the students will be researched on in a PBL course by the students in groups and will be presented in a poster session at the end of the term.
Literature
  • see lecture
Course L0898: Communication Networks Excercise
Typ Problem-based Learning
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dr. Maciej Mühleisen
Language EN
Cycle WiSe
Content Part of the content of the lecture Communication Networks are reflected in computing tasks in groups, others are motivated and addressed in the form of a PBL exercise.
Literature
  • announced during lecture

Module M0677: Digital Signal Processing and Digital Filters

Courses
Title Typ Hrs/wk CP
Digital Signal Processing and Digital Filters (L0446) Lecture 3 4
Digital Signal Processing and Digital Filters (L0447) Recitation Section (large) 1 2
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics 1-3
  • Signals and Systems
  • Fundamentals of signal and system theory as well as random processes.
  • Fundamentals of spectral transforms (Fourier series, Fourier transform, Laplace transform)
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know and understand basic algorithms of digital signal processing. They are familiar with the spectral transforms of discrete-time signals and are able to describe and analyse signals and systems in time and image domain. They know basic structures of digital filters and can identify and assess important properties including stability. They are aware of the effects caused by quantization of filter coefficients and signals. They are familiar with the basics of adaptive filters. They can perform traditional and parametric methods of spectrum estimation, also taking a limited observation window into account.
Skills The students are able to apply methods of digital signal processing to new problems. They can choose and parameterize suitable filter striuctures. In particular, the can design adaptive filters according to the minimum mean squared error (MMSE) criterion and develop an efficient implementation, e.g. based on the LMS or RLS algorithm.  Furthermore, the students are able to apply methods of spectrum estimation and to take the effects of a limited observation window into account.
Personal Competence
Social Competence

The students can jointly solve specific problems.

Autonomy

The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Microelectronics and Microsystems: Specialisation Microelectronics Complements: Elective Compulsory
Course L0446: Digital Signal Processing and Digital Filters
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Gerhard Bauch
Language EN
Cycle WiSe
Content
  • Transforms of discrete-time signals:

    • Discrete-time Fourier Transform (DTFT)

    • Discrete Fourier-Transform (DFT), Fast Fourier Transform (FFT)

    • Z-Transform

  • Correspondence of continuous-time and discrete-time signals, sampling, sampling theorem

  • Fast convolution, Overlap-Add-Method, Overlap-Save-Method

  • Fundamental structures and basic types of digital filters

  • Characterization of digital filters using pole-zero plots, important properties of digital filters

  • Quantization effects

  • Design of linear-phase filters

  • Fundamentals of stochastic signal processing and adaptive filters

    • MMSE criterion

    • Wiener Filter

    • LMS- and RLS-algorithm

  • Traditional and parametric methods of spectrum estimation

Literature

K.-D. Kammeyer, K. Kroschel: Digitale Signalverarbeitung. Vieweg Teubner.

V. Oppenheim, R. W. Schafer, J. R. Buck: Zeitdiskrete Signalverarbeitung. Pearson StudiumA. V.

W. Hess: Digitale Filter. Teubner.

Oppenheim, R. W. Schafer: Digital signal processing. Prentice Hall.

S. Haykin:  Adaptive flter theory.

L. B. Jackson: Digital filters and signal processing. Kluwer.

T.W. Parks, C.S. Burrus: Digital filter design. Wiley.

Course L0447: Digital Signal Processing and Digital Filters
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0839: Traffic Engineering

Courses
Title Typ Hrs/wk CP
Seminar Traffic Engineering (L0902) Seminar 2 2
Traffic Engineering (L0900) Lecture 2 2
Traffic Engineering Exercises (L0901) Recitation Section (small) 1 2
Module Responsible Prof. Andreas Timm-Giel
Admission Requirements None
Recommended Previous Knowledge
  • Fundamentals of communication or computer networks
  • Stochastics
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to describe methods for planning, optimisation and performance evaluation of communication networks.

Skills

Students are able to solve typical planning and optimisation tasks for communication networks. Furthermore they are able to evaluate the network performance using queuing theory.

Students are able to apply independently what they have learned to other and new problems. They can present their results in front of experts and discuss them.

Personal Competence
Social Competence
Autonomy

Students are able to acquire the necessary expert knowledge to understand the functionality and performance of new communication networks independently.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory
Course L0902: Seminar Traffic Engineering
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle WiSe
Content Selected applications of methods for planning, optimization, and performance evaluation of communication networks, which have been introduced in the traffic engineering lecture are prepared by the students and presented in a seminar.
Literature
  • U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Vieweg + Teubner
  • further literature announced in the lecture
Course L0900: Traffic Engineering
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle WiSe
Content

Network Planning and Optimization
• Linear Programming (LP)
• Network planning with LP solvers
• Planning of communication networks
Queueing Theory for Communication Networks
• Stochastic processes
• Queueing systems
• Switches (circuit- and packet switching)
• Network of queues

Literature

Literatur:
U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Springer
Weitere Literatur wird in der Lehrveranstaltung bekanntgegeben
/
 Literature:
U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Springer
further literature announced in the lecture

Course L0901: Traffic Engineering Exercises
Typ Recitation Section (small)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle WiSe
Content

Accompanying exercise for the traffic engineering course

Literature

Literatur:
U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Springer
Weitere Literatur wird in der Lehrveranstaltung bekanntgegeben / Literature:
U. Killat, Entwurf und Analyse von Kommunikationsnetzen, Springer
further literature announced in the lecture

Module M0738: Digital Audio Signal Processing

Courses
Title Typ Hrs/wk CP
Digital Audio Signal Processing (L0650) Lecture 3 4
Digital Audio Signal Processing (L0651) Recitation Section (large) 1 2
Module Responsible Prof. Udo Zölzer
Admission Requirements None
Recommended Previous Knowledge

Signals and Systems

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Die Studierenden können die grundlegenden Verfahren und Methoden der digitalen Audiosignalverarbeitung erklären. Sie können die wesentlichen physikalischen Effekte bei der Sprach- und Audiosignalverarbeitung erläutern und in Kategorien einordnen. Sie können einen Überblick der numerischen Methoden und messtechnischen Charakterisierung von Algorithmen zur Audiosignalverarbeitung geben. Sie können die erarbeiteten Algorithmen auf weitere Anwendungen im Bereich der Informationstechnik und Informatik abstrahieren.

Skills

The students will be able to apply methods and techniques from audio signal processing in the fields of mobile and internet communication. They can rely on elementary algorithms of audio signal processing in form of Matlab code and interactive JAVA applets. They can study parameter modifications and evaluate the influence on human perception and technical applications in a variety of applications beyond audio signal processing. Students can perform measurements in time and frequency domain in order to give objective and subjective quality measures with respect to the methods and applications.

Personal Competence
Social Competence

The students can work in small groups to study special tasks and problems and will be enforced to present their results with adequate methods during the exercise.

Autonomy

The students will be able to retrieve information out of the relevant literature in the field and putt hem into the context of the lecture. They can relate their gathered knowledge and relate them to other lectures (signals and systems, digital communication systems, image and video processing, and pattern recognition). They will be prepared to understand and communicate problems and effects in the field audio signal processing.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 45 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Course L0650: Digital Audio Signal Processing
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Udo Zölzer
Language EN
Cycle WiSe
Content
  • Introduction (Studio Technology,  Digital Transmission Systems, Storage Media, Audio Components at Home)

  • Quantization (Signal Quantization, Dither, Noise Shaping, Number Representation)

  • AD/DA Conversion (Methods, AD Converters, DA Converters, Audio Processing Systems, Digital Signal Processors, Digital Audio Interfaces, Single-Processor Systems, Multiprocessor Systems)

  • Equalizers (Recursive Audio Filters, Nonrecursive Audio Filters, Multi-Complementary Filter Bank)

  • Room Simulation (Early Reflections, Subsequent Reverberation, Approximation of Room Impulse Responses)

  • Dynamic Range Control (Static Curve, Dynamic Behavior, Implementation, Realization Aspects)

  • Sampling Rate Conversion (Synchronous Conversion, Asynchronous Conversion, Interpolation Methods)

  • Data Compression (Lossless Data Compression, Lossy Data Compression, Psychoacoustics, ISO-MPEG1 Audio Coding)

Literature

- U. Zölzer, Digitale Audiosignalverarbeitung, 3. Aufl., B.G. Teubner, 2005.

- U. Zölzer, Digitale Audio Signal Processing, 2nd Edition, J. Wiley & Sons, 2005.


- U. Zölzer (Ed), Digital Audio Effects, 2nd Edition, J. Wiley & Sons, 2011.


 






Course L0651: Digital Audio Signal Processing
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Udo Zölzer
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Specialization Nanoelectronics and Microsystems Technology


The students of this specialization are introduced into the design of CMOS integrated circuits and the most important manufacturing steps. They gain knowledge and competences regarding the software tools for simulation and of their structure by performing classroom projects. A solid awareness of possible reliability problems and how to prevent them belongs to the acquired competences. Furthermore, the students get competences in the field of microsystem technology and in the usage of software tools for the design of those microsystems. The students acquire the necessary knowledge to develop as well as challenging integrated circuits and microsystems and to combine both to innovative units.

Module M0578: Integrated Circuits

Courses
Title Typ Hrs/wk CP
Integrated Circuits (L0207) Lecture 2 3
Module Responsible Dr. Dietmar Schröder
Admission Requirements
Recommended Previous Knowledge

Circuit Design, Computer Engineering, Signals and Systems

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students can explicate the basic relationships of price and performance of integrated circuits using suitable figures of merit. They can explain the interrelationships of global and local manufacturing tolerances, matching, and mismatch. They are able to describe a hierarchical system and how such systems - integrated circuits in particular - are designed. Students can specify the components of project management und explain the purposes of these.
Skills Students can compute the expected mismatch of two equally designed integrated devices. They can calculate the noise spectra of voltages and currents in electronic networks. They are able to design hierarchical electronic circuits and to verify these by simulation. They can participate meaningfully in a systematically planned and executed project and provide own contributions to achieving the project goals.
Personal Competence
Social Competence Students can cooperate meaningfully and purposefully with other members in a project team. They respect project structures and schedules as well as other rules in the project. They are able to document and present their own work comprehensibly for others. In discussions, they can respectfully pass and constructively accept criticism.
Autonomy Students are able to acquire necessary informations from sources provided und to put them into context with the task at hand. They can autonomously familiarize themselves with the details of the design software and systematically troubleshoot their circuits.
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Examination Oral exam
Examination duration and scale 30 minutes individual oral exam
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Course L0207: Integrated Circuits
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Dietmar Schröder
Language DE
Cycle SoSe
Content
  • Semiconductor Technologies: Price-Performance-Ratio, Performance and Figures of Merit, Mismatch and Noise
  • System Design (concept of systems, hierarchical design)
  • Project Management of Design Projects (planning, monitoring, control)
Literature

R.J. Baker, CMOS: circuit, design, layout and simulation. IEEE Press, 2010.

F. Daenzer (Ed.)., Systems Engineering. Verlag Industrielle Organisation, 1986.

M. Burghardt, Projektmanagement. Siemens, 1993.

Module M0643: Optoelectronics I - Wave Optics

Courses
Title Typ Hrs/wk CP
Optoelectronics I: Wave Optics (L0359) Lecture 2 3
Optoelectronics I: Wave Optics (Problem Solving Course) (L0361) Recitation Section (small) 1 1
Module Responsible Prof. Manfred Eich
Admission Requirements

Keine

Recommended Previous Knowledge

Basics in electrodynamics, calculus


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the fundamental mathematical and physical relations of freely propagating optical waves.
They can give an overview on wave optical phenomena such as diffraction, reflection and refraction, etc. 
Students can describe waveoptics based components such as electrooptical modulators in an application oriented way.



Skills

Students can generate models and derive mathematical descriptions in relation to free optical wave propagation.
They can derive approximative solutions and judge factors influential on the components' performance.


Personal Competence
Social Competence

Students can jointly solve subject related problems in groups. They can present their results effectively within the framework of the problem solving course.


Autonomy

Students are capable to extract relevant information from the provided references and to relate this information to the content of the lecture. They can reflect their acquired level of expertise with the help of lecture accompanying measures such as exam typical exam questions. Students are able to connect their knowledge with that acquired from other lectures.


Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Written exam
Examination duration and scale 40 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Materials Science: Specialisation Nano and Hybrid Materials: Elective Compulsory
Microelectronics and Microsystems: Specialisation Microelectronics Complements: Elective Compulsory
Course L0359: Optoelectronics I: Wave Optics
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Manfred Eich
Language EN
Cycle SoSe
Content
  • Introduction to optics
  • Electromagnetic theory of light
  • Interference
  • Coherence
  • Diffraction
  • Fourier optics
  • Polarisation and Crystal optics
  • Matrix formalism
  • Reflection and transmission
  • Complex refractive index
  • Dispersion
  • Modulation and switching of light
Literature

Bahaa E. A. Saleh, Malvin Carl Teich, Fundamentals of Photonics, Wiley 2007 
Hecht, E., Optics, Benjamin Cummings, 2001
Goodman, J.W. Statistical Optics, Wiley, 2000
Lauterborn, W., Kurz, T., Coherent Optics: Fundamentals and Applications, Springer, 2002

Course L0361: Optoelectronics I: Wave Optics (Problem Solving Course)
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Manfred Eich
Language EN
Cycle SoSe
Content see lecture Optoelectronics 1 - Wave Optics
Literature

see lecture Optoelectronics 1 - Wave Optics

Module M0925: Design of Highly Complex Integrated Systems and CAD Tools

Courses
Title Typ Hrs/wk CP
CAD Tools (L0698) Lecture 2 3
Design of Highly Complex Integrated Systems (L0699) Lecture 2 3
Module Responsible Prof. Volkhard Klinger
Admission Requirements
Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
Skills
Personal Competence
Social Competence
Autonomy
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 40 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Microelectronics and Microsystems: Specialisation Microelectronics Complements: Elective Compulsory
Course L0698: CAD Tools
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Volkhard Klinger
Language EN
Cycle WiSe
Content
Literature
Course L0699: Design of Highly Complex Integrated Systems
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Volkhard Klinger
Language EN
Cycle SoSe
Content
Literature

Module M0747: Microsystem Design

Courses
Title Typ Hrs/wk CP
Microsystem Design (L0683) Lecture 2 3
Microsystem Design (L0684) Laboratory Course 3 3
Module Responsible Prof. Manfred Kasper
Admission Requirements
Recommended Previous Knowledge

Mathematical Calculus, Linear Algebra, Microsystem Engineering

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students know about the most important and most common simulation and design methods used in microsystem design. The scientific background of finite element methods and the basic theory of these methods are known.

Skills

Students are able to apply simulation methods and commercial simulators in a goal oriented approach to complex design tasks. Students know to apply the theory in order achieve estimates of expected accuracy and can judge and verify the correctness of results. Students are able to develop a design approach even if only incomplete information about material data or constraints are available. Student can make use of approximate and reduced order models in a preliminary design stage or a system simulation.

Personal Competence
Social Competence

Students are able to solve specific problems alone or in a group and to present the results accordingly. Students can develop and explain their solution approach and subdivide the design task to subproblems which are solved separately by group members.

Autonomy

Students are able to acquire particular knowledge using specialized literature and to integrate and associate this knowledge with other fields.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Oral exam
Examination duration and scale halbstündig
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0683: Microsystem Design
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Manfred Kasper
Language EN
Cycle SoSe
Content

Finite difference methods

Approximation error

Finite element method

Order of convergence

Error estimation, mesh refinement

Makromodeling

Reduced order modeling

Black-box models

System identification

Multi-physics systems

System simulation

Levels of simulation, network simulation

Transient problems

Non-linear problems

Introduction to Comsol

Application to thermal, electric, electromagnetic, mechanical and fluidic problems

Literature

M. Kasper: Mikrosystementwurf, Springer (2000)

S. Senturia: Microsystem Design, Kluwer (2001)

Course L0684: Microsystem Design
Typ Laboratory Course
Hrs/wk 3
CP 3
Workload in Hours Independent Study Time 48, Study Time in Lecture 42
Lecturer Prof. Manfred Kasper
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0761: Semiconductor Technology

Courses
Title Typ Hrs/wk CP
Semiconductor Technology (L0722) Lecture 4 5
Semiconductor Technology (L0723) Laboratory Course 2 2
Module Responsible Prof. Hoc Khiem Trieu
Admission Requirements

None

Recommended Previous Knowledge

Basics in physics, chemistry, material science and semiconductor devices

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge


Students are able

     to describe and to explain current fabrication techniques for Si and GaAs substrates,

     to discuss in details the relevant fabrication processes, process flows and the impact thereof on the fabrication of semiconductor devices and integrated circuits and

     to present integrated process flows.


Skills


Students are capable

     to analyze the impact of process parameters on the processing results,

     to select and to evaluate processes and

     to develop process flows for the fabrication of semiconductor devices.


Personal Competence
Social Competence


Students are able to prepare and perform their lab experiments in team work as well as to present and discuss the results in front of audience.


Autonomy None
Workload in Hours Independent Study Time 126, Study Time in Lecture 84
Credit points 7
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Course L0722: Semiconductor Technology
Typ Lecture
Hrs/wk 4
CP 5
Workload in Hours Independent Study Time 94, Study Time in Lecture 56
Lecturer Prof. Hoc Khiem Trieu
Language DE/EN
Cycle SoSe
Content
  • Introduction (historical view and trends in microelectronics)
  • Basics in material science (semiconductor, crystal, Miller indices, crystallographic defects)
  • Crystal fabrication (crystal pulling for Si and GaAs: impurities, purification, Czochralski , Bridgeman and float zone process)
  • Wafer fabrication (process flow, specification, SOI)
  • Fabrication processes
  • Doping (energy band diagram, doping, doping by alloying, doping by diffusion: transport processes, doping profile, higher order effects and process technology, ion implantation: theory, implantation profile, channeling, implantation damage, annealing and equipment)

  • Oxidation (silicon dioxide: structure, electrical properties and oxide charges, thermal oxidation: reactions, kinetics, influences on growth rate, process technology and equipment, anodic oxidation, plasma oxidation, thermal oxidation of GaAs)

  • Deposition techniques (theory: nucleation, film growth and structure zone model, film growth process, reaction kinetics, temperature dependence and equipment; epitaxy: gas phase, liquid phase, molecular beam epitaxy; CVD techniques: APCVD, LPCVD, deposition of metal silicide, PECVD and LECVD; basics of plasma, equipment, PVD techniques: high vacuum evaporation, sputtering)

  • Structuring techniques (subtractive methods, photolithography: resist properties, printing techniques: contact, proximity and projection printing, resolution limit, practical issues and equipment, additive methods: liftoff technique and electroplating, improving resolution: excimer laser light source, immersion lithography and phase shift lithography, electron beam lithography, X-ray lithography, EUV lithography, ion beam lithography, wet chemical etching: isotropic and anisotropic, corner undercutting, compensation masks and etch stop techniques; dry etching: plasma enhanced etching, backsputtering, ion milling, chemical dry etching, RIE, sidewall passivation)

  • Process integration (CMOS process, bipolar process)

  • Assembly and packaging technology (hierarchy of integration, packages, chip-on-board, chip assembly, electrical contact: wire bonding, TAB and flip chip, wafer level package, 3D stacking)

     

Literature

S.K. Ghandi: VLSI Fabrication principles – Silicon and Gallium Arsenide, John Wiley & Sons

S.M. Sze: Semiconductor Devices – Physics and Technology, John Wiley & Sons

U. Hilleringmann: Silizium-Halbleitertechnologie, Teubner Verlag

H. Beneking: Halbleitertechnologie – Eine Einführung in die Prozeßtechnik von Silizium und III-V-Verbindungen, Teubner Verlag

K. Schade: Mikroelektroniktechnologie, Verlag Technik Berlin

S. Campbell: The Science and Engineering of Microelectronic Fabrication, Oxford University Press

P. van Zant: Microchip Fabrication – A Practical Guide to Semiconductor Processing, McGraw-Hill

Course L0723: Semiconductor Technology
Typ Laboratory Course
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Hoc Khiem Trieu
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0800: Numerical Methods for Electromagnetic Field Computation

Courses
Title Typ Hrs/wk CP
Numerical Methods for Electromagnetic Field Computation (L0802) Lecture 2 3
Numerical Methods for Electromagnetic Field Computation (L0803) Recitation Section (large) 1 1
Module Responsible Dr. Heinz-Dietrich Brüns
Admission Requirements

None

Recommended Previous Knowledge Basic principles of electromagnetic field theory
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Numerical methods in numerical field computation  are of increasing importance in electrical engineering, for example in the are of antenna development or for analyzing electromagnetic compatibility problems (EMC). The underlying principles of the major techniques that are currently applied in practice are explained. It turns out that each method has its strengths and weaknesses in relation to specific applications. The students shall be enabled to evaluate which kind of method could be advantageous for a certain case and if an application concerning a certain problem area is manageable at all.

Skills

The students will be able to set up discretized models based on the working principle of the chosen numerical method. This is carried out regarding the electrical size and considering the geometrical complexity. The students know the  interrelationship between the number of grid elements (surface patches, cells), the necessary memory resulting form this and the computation time. They are aware of the requirements of the method under consideration to achieve convergent results and they learn to validate these results using various techniques. The students are able to distinguish between methods that are used in the time domain, in the frequency domain and in the range of electrostatics. Furthermore the students know the advantages, possibilities and constraints of surface and volume based techniques.

Personal Competence
Social Competence

In practical exercises small groups of students can apply the program system CONCEPT-II, which is based on one of the most important techniques, the so-called method of moments. The program is under continuous development at the Institute of Electromagnetic Theory.

Autonomy

The students are able to generally apply their new knowledge in electromagnetics and to associate it with other courses. On the basis of the introduction given in the lecture they are capable to easily learn more about a technique from the given literature.

Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Oral exam
Examination duration and scale 30 Minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Course L0802: Numerical Methods for Electromagnetic Field Computation
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle SoSe
Content

-Short and in details more comprehensive repetition of relevant fields of electromagnetic theory
-Introduction into the finite difference method with emphasis on electrostatics and into the charge simulation method
-Basics of the boundary element method in electrostatics
-Hygens principle, magnetic currents in numerics
-FDTD, FIT (finite integration technique) as important techniques for time domain applications
-Finite element method (FEM)
-The method of moments in the frequency domain
-TLM in the time domain
-Possibilities for validating numerical solutions
-Application of hybrid techniques in special problem areas

Literature

Allen Tavlove, Susan C. Hagness: Computational Electrodynamics: The Finite-Difference
Time-Domain Method, Artech House Inc., 2005

Walton C. Gibson: The Method of Moments in Electromagnetics, Chapman & Hall/CRC

Ianming Jin: The Finite Element Method in Electromagnetics, John Wiley & Sons, Inc.,
second edition, 2002

Pei-bai Zhou: Numerical Analysis of Electromagnetic Fields, Springer-Verlag, 1993

C. Christopoulos: The Transmission-Line Modeling (TLM) Method in Electromagnetics,
Morgan&Claypool Publishers, 2006

Course L0803: Numerical Methods for Electromagnetic Field Computation
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Dr. Heinz-Dietrich Brüns
Language DE/EN
Cycle SoSe
Content

-Short and in details more comprehensive repetition of relevant fields of electromagnetic theory
-Introduction into the finite difference method with emphasis on electrostatics and into the charge simulation method
-Basics of the boundary element method in electrostatics
-Hygens principle, magnetic currents in numerics
-FDTD, FIT (finite integration technique) as important techniques for time domain applications
-Finite element method (FEM)
-The method of moments in the frequency domain
-TLM in the time domain
-Possibilities for validating numerical solutions
-Application of hybrid techniques in special problem areas

Literature

Allen Tavlove, Susan C. Hagness: Computational Electrodynamics: The Finite-Difference
Time-Domain Method, Artech House Inc., 2005

Walton C. Gibson: The Method of Moments in Electromagnetics, Chapman & Hall/CRC

Ianming Jin: The Finite Element Method in Electromagnetics, John Wiley & Sons, Inc.,
second edition, 2002

Pei-bai Zhou: Numerical Analysis of Electromagnetic Fields, Springer-Verlag, 1993

C. Christopoulos: The Transmission-Line Modeling (TLM) Method in Electromagnetics,
Morgan&Claypool Publishers, 2006

Module M0919: Laboratory: Analog and Digital Circuit Design

Courses
Title Typ Hrs/wk CP
Laboratory: Analog Circuit Design (L0692) Laboratory Course 2 3
Laboratory: Digital Circuit Design (L0694) Laboratory Course 2 3
Module Responsible Prof. Wolfgang Krautschneider
Admission Requirements None
Recommended Previous Knowledge Basic knowledge of semiconductor devices and circuit design
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the structure and philosophy of the software framework for circuit design.
  • Students can determine all necessary input parameters for circuit simulation.
  • Students know the basics physics of the analog behavior.
  • Students are able to explain the functions of the logic gates of their digital design.
  • Students can explain the algorithms of checking routines.
  • Students are able to select the appropriate transistor models for fast and accurate simulations.


Skills
  • Students can activate and execute all necessary checking routines for verification of proper circuit functionality.
  • Students are able to run the input desks for definition of their electronic circuits.
  • Students can define the specifications of the electronic circuits to be designed.
  • Students can optimize the electronic circuits for low-noise and low-power.
  • Students can develop analog circuits for mobile medical applications.
  • Students can define the building blocks of digital systems.


Personal Competence
Social Competence
  • Students are trained to work through complex circuits in teams.
  • Students are able to share their knowledge for efficient design work.
  • Students can help each other to understand all the details and options of the design software.
  • Students are aware of their limitations regarding circuit design, so they do not go ahead, but they involve experts when required.
  • Students can present their design approaches for easy checking by more experienced experts.


Autonomy
  • Students are able to realistically judge the status of their knowledge and to define actions for improvements when necessary.
  • Students can break down their design work in sub-tasks and can schedule the design work in a realistic way.
  • Students can handle the complex data structures of their design task and document it in consice but understandable way.
  • Students are able to judge the amount of work for a major design project.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 60 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0692: Laboratory: Analog Circuit Design
Typ Laboratory Course
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Wolfgang Krautschneider
Language DE
Cycle WiSe
Content
  • Input desk for circuits
  • Algorithms for simulation
  • MOS transistor model
  • Simulation of analog circuits
  • Placement and routing     
  • Generation of layouts
  • Design checking routines
  • Postlayout simulations



Literature Handouts to be distributed
Course L0694: Laboratory: Digital Circuit Design
Typ Laboratory Course
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Wolfgang Krautschneider
Language DE
Cycle SoSe
Content
  • Definition of specifications
  • Architecture studies
  • Digital simulation flow
  • Philosophy of standard cells
  • Placement and routing of standard cells
  • Layout generation
  • Design checking routines


Literature Handouts will be distributed

Module M0918: Fundamentals of IC Design

Courses
Title Typ Hrs/wk CP
Fundamentals of IC Design (L0766) Lecture 2 3
Fundamentals of IC Design (L1057) Laboratory Course 2 3
Module Responsible Prof. Wolfgang Krautschneider
Admission Requirements None
Recommended Previous Knowledge Fundamentals of electrical engineering, electronic devices and circuits
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the basic structure of the circuit simulator SPICE.
  • Students are able to describe the differences between the MOS transistor models of the circuit simulator SPICE.
  • Students can discuss the different concept for realization the hardware of electronic circuits.
  • Students can exemplify the approaches for “Design for Testability”.
  • Students can specify models for calculation of the reliability of electronic circuits.


Skills
  • Students can determine the input parameters for the circuit simulation program SPICE.
  • Students can select the most appropriate MOS modelling approaches for circuit simulations.
  • Students can quantify the trade-off of different design styles.
  • Students can determine the lot sizes and costs for reliability analysis.


Personal Competence
Social Competence
  • Students can compile design studies by themselves or together with partners.
  • Students are able to select the most efficient design methodology for a given task.
  • Students are able to define the work packages for design teams.


Autonomy
  • Students are able to assess the strengths and weaknesses of their design work in a self-contained manner.
  • Students can name and bring together all the tools required for total design flow.


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 40 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0766: Fundamentals of IC Design
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Wolfgang Krautschneider
Language DE/EN
Cycle SoSe
Content
  • Circuit-Simulator SPICE 
  • SPICE-Models for MOS transistors
  • IC design
  • Technology of MOS circuits
  • Standard cell design
  • Design of gate arrays
  • Examples for realization of ASICs in the institute of nanoelectronics
  • Reliability of integrated circuits
  • Testing of integrated circuits
Literature

R. J. Baker, „CMOS-Circuit Design, Layout, and Simulation“, Wiley & Sons, IEEE Press, 2010 

X. Liu, VLSI-Design Methodology Demystified; IEEE, 2009

N. Van Helleputte, J. M. Tomasik, W. Galjan, A. Mora-Sanchez, D. Schroeder, W. H. Krautschneider, R. Puers, A flexible system-on-chip (SoC) for biomedical signal acquisition and processing, Sensors and Actuators A: Physical, vol. 142, p. 361-368, 2008.


Course L1057: Fundamentals of IC Design
Typ Laboratory Course
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Wolfgang Krautschneider
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0930: Semiconductor Seminar

Courses
Title Typ Hrs/wk CP
Semiconductor Seminar (L0760) Seminar 2 2
Module Responsible Dr. Dietmar Schröder
Admission Requirements
Recommended Previous Knowledge

Bachelor of Science

Semiconductors

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge Students can explain the most important facts and relationships of a specific topic from the field of semiconductors.
Skills

Students are able to compile a specified topic from the field of semiconductors and to give a clear, structured and comprehensible presentation of the subject. They can comply with a given duration of the presentation. They can write in English a summary including illustrations that contains the most important results, relationships and explanations of the subject.

Personal Competence
Social Competence Students are able to adapt their presentation with respect to content, detailedness, and presentation style to the composition and previous knowledge of the audience. They can answer questions from the audience in a curt and precise manner.
Autonomy Students are able to autonomously carry out a literature research concerning a given topic. They can independently evaluate the material. They can self-reliantly decide which parts of the material should be included in the presentation.
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Presentation
Examination duration and scale 15 minutesw presentation + 5-10 minutes discussion + 2 pages written abstract
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Materials Science: Specialisation Nano and Hybrid Materials: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0760: Semiconductor Seminar
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dr. Dietmar Schröder, Prof. Manfred Kasper, Prof. Wolfgang Krautschneider, Prof. Manfred Eich, Prof. Hoc Khiem Trieu
Language EN
Cycle SoSe
Content

Prepare, present, and discuss talks about recent topics from the field of semiconductors. The presentations must be given in English.

Evaluation Criteria:

  • understanding of subject, discussion, response to questions
  • structure and logic of presentation (clarity, precision)
  • coverage of the topic, selection of subjects presented
  • linguistic presentation (clarity, comprehensibility)
  • visual presentation (clarity, comprehensibility)
  • handout (see below)
  • compliance with timing requirement.

Handout:
Before your presentation, it is mandatory to distribute a printed
handout (short abstract) of your presentation in English language. This must be no
longer than two pages A4, and include the most important results,
conclusions, explanations and diagrams.

Literature

Aktuelle Veröffentlichungen zu dem gewählten Thema

Module M0935: Microcontroller Circuits: Implementation in Hardware and Software

Courses
Title Typ Hrs/wk CP
Microcontroller Circuits: Implementation in Hardware and Software (L0087) Seminar 2 2
Module Responsible Prof. Siegfried Rump
Admission Requirements none.
Recommended Previous Knowledge lecture: Computer Architectures
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students can describe parts and operation of a common family of microcontrollers. They know details about operations of CPUs, and they can transfer algorithms to machine code.
Skills

The students can design and use electronic circuits (digital with some analogue parts). Furthermore they are able to implement solutions of some tasks by way of assembler programming on these circuits.

Personal Competence
Social Competence

Groups of two students work on special projects. The students have the skill to separate the project into smaller parts and to present the achieved results in an appropriate short talk.

Autonomy The student can use, select and estimate suitable sources, which are available from information technology companies. They apply those findings to their projects.
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Written elaboration
Examination duration and scale 15 minutes + disputation
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Course L0087: Microcontroller Circuits: Implementation in Hardware and Software
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe/SoSe
Content
Literature

Module M0644: Optoelectronics II - Quantum Optics

Courses
Title Typ Hrs/wk CP
Optoelectronics II: Quantum Optics (L0360) Lecture 2 3
Optoelectronics II: Quantum Optics (Problem Solving Course) (L0362) Recitation Section (small) 1 1
Module Responsible Prof. Manfred Eich
Admission Requirements None
Recommended Previous Knowledge

Basic principles of electrodynamics, optics and quantum mechanics

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students can explain the fundamental mathematical and physical relations of quantum optical phenomena such as absorption, stimulated and spontanous emission. They can describe material properties as well as technical solutions. They can give an overview on quantum optical components in technical applications.

Skills

Students can generate models and derive mathematical descriptions in relation to quantum optical phenomena and processes. They can derive approximative solutions and judge factors influential on the components' performance.


Personal Competence
Social Competence

Students can jointly solve subject related problems in groups. They can present their results effectively within the framework of the problem solving course.


Autonomy

Students are capable to extract relevant information from the provided references and to relate this information to the content of the lecture. They can reflect their acquired level of expertise with the help of lecture accompanying measures such as exam typical exam questions. Students are able to connect their knowledge with that acquired from other lectures.


Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Written exam
Examination duration and scale 40 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Materials Science: Specialisation Nano and Hybrid Materials: Elective Compulsory
Microelectronics and Microsystems: Specialisation Microelectronics Complements: Elective Compulsory
Course L0360: Optoelectronics II: Quantum Optics
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Manfred Eich
Language EN
Cycle WiSe
Content
  • Generation of light
  • Photons
  • Thermal and nonthermal light
  • Laser amplifier
  • Noise
  • Optical resonators
  • Spectral properties of laser light
  • CW-lasers (gas, solid state, semiconductor)
  • Pulsed lasers
Literature

Bahaa E. A. Saleh, Malvin Carl Teich, Fundamentals of Photonics, Wiley 2007
Demtröder, W., Laser Spectroscopy: Basic Concepts and Instrumentation, Springer, 2002
Kasap, S.O., Optoelectronics and Photonics: Principles and Practices, Prentice Hall, 2001
Yariv, A., Quantum Electronics, Wiley, 1988
Wilson, J., Hawkes, J., Optoelectronics: An Introduction, Prentice Hall, 1997, ISBN: 013103961X
Siegman, A.E., Lasers, University Science Books, 1986

Course L0362: Optoelectronics II: Quantum Optics (Problem Solving Course)
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Manfred Eich
Language EN
Cycle WiSe
Content see lecture Optoelectronics 1 - Wave Optics
Literature

see lecture Optoelectronics 1 - Wave Optics

Module M0768: Microsystems Technology in Theory and Practice

Courses
Title Typ Hrs/wk CP
Microsystems Technology (L0724) Lecture 2 4
Microsystems Technology (L0725) Problem-based Learning 2 2
Module Responsible Prof. Hoc Khiem Trieu
Admission Requirements None
Recommended Previous Knowledge

Basics in physics, chemistry, mechanics and semiconductor technology

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able

     to present and to explain current fabrication techniques for microstructures and especially methods for the fabrication of microsensors and microactuators, as well as the integration thereof in more complex systems

     to explain in details operation principles of microsensors and microactuators and

     to discuss the potential and limitation of microsystems in application.


Skills

Students are capable

     to analyze the feasibility of microsystems,

     to develop process flows for the fabrication of microstructures and

     to apply them.




Personal Competence
Social Competence


Students are able to prepare and perform their lab experiments in team work as well as to present and discuss the results in front of audience.


Autonomy

None

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Microelectronics and Microsystems: Core qualification: Elective Compulsory
Course L0724: Microsystems Technology
Typ Lecture
Hrs/wk 2
CP 4
Workload in Hours Independent Study Time 92, Study Time in Lecture 28
Lecturer Prof. Hoc Khiem Trieu
Language EN
Cycle WiSe
Content
  • Introduction (historical view, scientific and economic relevance, scaling laws)
  • Semiconductor Technology Basics, Lithography (wafer fabrication, photolithography, improving resolution, next-generation lithography, nano-imprinting, molecular imprinting)
  • Deposition Techniques (thermal oxidation, epitaxy, electroplating, PVD techniques: evaporation and sputtering; CVD techniques: APCVD, LPCVD, PECVD and LECVD; screen printing)
  • Etching and Bulk Micromachining (definitions, wet chemical etching, isotropic etch with HNA, electrochemical etching, anisotropic etching with KOH/TMAH: theory, corner undercutting, measures for compensation and etch-stop techniques; plasma processes, dry etching: back sputtering, plasma etching, RIE, Bosch process, cryo process, XeF2 etching)
  • Surface Micromachining and alternative Techniques (sacrificial etching, film stress, stiction: theory and counter measures; Origami microstructures, Epi-Poly, porous silicon, SOI, SCREAM process, LIGA, SU8, rapid prototyping)
  • Thermal and Radiation Sensors (temperature measurement, self-generating sensors: Seebeck effect and thermopile; modulating sensors: thermo resistor, Pt-100, spreading resistance sensor, pn junction, NTC and PTC; thermal anemometer, mass flow sensor, photometry, radiometry, IR sensor: thermopile and bolometer)
  • Mechanical Sensors (strain based and stress based principle, capacitive readout, piezoresistivity,  pressure sensor: piezoresistive, capacitive and fabrication process; accelerometer: piezoresistive, piezoelectric and capacitive; angular rate sensor: operating principle and fabrication process)
  • Magnetic Sensors (galvanomagnetic sensors: spinning current Hall sensor and magneto-transistor; magnetoresistive sensors: magneto resistance, AMR and GMR, fluxgate magnetometer)
  • Chemical and Bio Sensors (thermal gas sensors: pellistor and thermal conductivity sensor; metal oxide semiconductor gas sensor, organic semiconductor gas sensor, Lambda probe, MOSFET gas sensor, pH-FET, SAW sensor, principle of biosensor, Clark electrode, enzyme electrode, DNA chip)
  • Micro Actuators, Microfluidics and TAS (drives: thermal, electrostatic, piezo electric and electromagnetic; light modulators, DMD, adaptive optics, microscanner, microvalves: passive and active, micropumps, valveless micropump, electrokinetic micropumps, micromixer, filter, inkjet printhead, microdispenser, microfluidic switching elements, microreactor, lab-on-a-chip, microanalytics)
  • MEMS in medical Engineering (wireless energy and data transmission, smart pill, implantable drug delivery system, stimulators: microelectrodes, cochlear and retinal implant; implantable pressure sensors, intelligent osteosynthesis, implant for spinal cord regeneration)
  • Design, Simulation, Test (development and design flows, bottom-up approach, top-down approach, testability, modelling: multiphysics, FEM and equivalent circuit simulation; reliability test, physics-of-failure, Arrhenius equation, bath-tub relationship)
  • System Integration (monolithic and hybrid integration, assembly and packaging, dicing, electrical contact: wire bonding, TAB and flip chip bonding; packages, chip-on-board, wafer-level-package, 3D integration, wafer bonding: anodic bonding and silicon fusion bonding; micro electroplating, 3D-MID)


Literature

M. Madou: Fundamentals of Microfabrication, CRC Press, 2002

N. Schwesinger: Lehrbuch Mikrosystemtechnik, Oldenbourg Verlag, 2009

T. M. Adams, R. A. Layton:Introductory MEMS, Springer, 2010

G. Gerlach; W. Dötzel: Introduction to microsystem technology, Wiley, 2008

Course L0725: Microsystems Technology
Typ Problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Hoc Khiem Trieu
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0797: Research Project in Nanoelectronics and Microsystems Technology

Courses
Title Typ Hrs/wk CP
Module Responsible Dozenten des SD E
Admission Requirements None
Recommended Previous Knowledge

Advanced state of knowledge in the electrical engineering master program


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students know current research topics oft institutes engaged in their specialization. They can name the fundamental scientific methods used for doing related reserach.


Skills

Students are capable of completing a small, independent sub-project of currently ongoing research projects in the institutes engaged in their specialization. Students can justify and explain their approach for problem solving, they can draw conclusions from their results, and then can find new ways and methods for their work. Students are capable of comparing and assessing alterantive approaches with their own with regard to given criteria.


Personal Competence
Social Competence

Students are able to discuss their work progress with research assistants of the supervising institute .  They are capable of presenting their results in front of a professional audience.


Autonomy

Based on their competences gained so far students are capable of defining meaningful tasks within ongoing research project for themselves. They are able to develop the necessary understanding  and problem solving methods.


Workload in Hours Independent Study Time 180, Study Time in Lecture 0
Credit points 6
Examination Project (accord. to Subject Specific Regulations)
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory

Module M0781: EMC II: Signal Integrity and Power Supply of Electronic Systems

Courses
Title Typ Hrs/wk CP
EMC II: Signal Integrity and Power Supply of Electronic Systems (L0770) Lecture 3 4
EMC II: Signal Integrity and Power Supply of Electronic Systems (L0771) Recitation Section (small) 1 1
EMC II: Signal Integrity and Power Supply of Electronic Systems (L0774) Laboratory Course 1 1
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge

Fundamentals of electrical engineering


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain the fundamental principles, inter-dependencies, and methods of signal and power integrity of electronic systems. They are able to relate signal and power integrity to the context of interference-free design of such systems, i.e. their electromagnetic compatibility. They are capable of explaining the basic behavior of signals and power supply in typical packages and interconnects. They are able to propose and describe problem solving strategies for signal and power integrity issues. They are capable of giving an overview over measurement and simulation methods for characterization of signal and power integrity in electrical engineering practice.


Skills

Students are able to apply a series of modeling methods for characterization of electromagnetic field behavior in packages and interconnect structure of electronic systems. They are able to determine the most important effects that these models are predicting in terms of signal and power integrity. They can classify these effects and they can quantitatively analyze them. They are capable of deriving problem solving strategies from these predictions and they can adapt them to applications in electrical engineering practice. The can evaluate their problem solving strategies against each other.


Personal Competence
Social Competence

Students are able to work together on subject related tasks in small groups. They are able to present their results effectively in English (e.g. during CAD exercises).


Autonomy

Students are capable to gather necessary information from the references provided and relate that information to the context of the lecture. They are able to make a connection between their knowledge obtained in this lecture with the content of other lectures (e.g. theory of electromagnetic fields, communications, and semiconductor circuit design). They can communicate problems and solutions in the field of signal integrity and power supply of interconnect and packages in English.


Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Oral exam
Examination duration and scale 30-60 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Course L0770: EMC II: Signal Integrity and Power Supply of Electronic Systems
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle WiSe
Content

- The role of packages and interconnects in electronic systems

- Components of packages and interconnects in electronic systems

- Main goals and concepts of signal and power integrity of electronic systems

- Repeat of relevant concepts from the theory electromagnetic fields

- Properties of digital signals and systems

- Design and characterization of signal integrity

- Design and characterization of power supply

- Techniques and devices for measurements in time- and frequency-domain

- CAD tools for electrical analysis and design of packages and interconnects

- Connection to overall electromagnetic compatibility of electronic systems


Literature

- J. Franz, "EMV: Störungssicherer Aufbau elektronischer Schaltungen", Springer (2012)

- R. Tummala, "Fundamentals of Microsystems Packaging", McGraw-Hill (2001)

- S. Ramo, J. Whinnery, T. Van Duzer, "Fields and Waves in Communication Electronics", Wiley (1994)

- S. Thierauf, "Understanding Signal Integrity", Artech House (2010)

- M. Swaminathan, A. Engin, "Power Integrity Modeling and Design for Semiconductors and Systems", Prentice-Hall (2007)


Course L0771: EMC II: Signal Integrity and Power Supply of Electronic Systems
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course
Course L0774: EMC II: Signal Integrity and Power Supply of Electronic Systems
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Christian Schuster
Language DE/EN
Cycle WiSe
Content

- The role of packages and interconnects in electronic systems

- Components of packages and interconnects in electronic systems

- Main goals and concepts of signal and power integrity of electronic systems

- Repeat of relevant concepts from the theory electromagnetic fields

- Properties of digital signals and systems

- Design and characterization of signal integrity

- Design and characterization of power supply

- Techniques and devices for measurements in time- and frequency-domain

- CAD tools for electrical analysis and design of packages and interconnects

- Connection to overall electromagnetic compatibility of electronic systems


Literature

- J. Franz, "EMV: Störungssicherer Aufbau elektronischer Schaltungen", Springer (2012)

- R. Tummala, "Fundamentals of Microsystems Packaging", McGraw-Hill (2001)

- S. Ramo, J. Whinnery, T. Van Duzer, "Fields and Waves in Communication Electronics", Wiley (1994)

- S. Thierauf, "Understanding Signal Integrity", Artech House (2010)

- M. Swaminathan, A. Engin, "Power Integrity Modeling and Design for Semiconductors and Systems", Prentice-Hall (2007)


Specialization Control and Power Systems

This specialization offers a wide range of topics with respect to various concepts of control and electric power systems, process measurement, robotics, communication networks and digital signal processing.

Students are enabled to analyze, to model and to simulate complex dynamical systems like electric power systems. Moreover, they acquire a profound knowledge about various methods to monitor and control complex systems and to specifically influence their dynamic behavior. In addition, they are able to understand information systems and their recent technologies used in electrical power engineering and develop innovative approaches for smart grids.

As a result, the students will have the skills to entirely analyze, design and optimize all aspects of control and electric power systems. In today’s age of increasing digitalization, automation and communication within many branches of industry especially towards a sustainable electrical power supply, this expertise is of outstanding importance for positions in industry and academia.

Module M0692: Approximation and Stability

Courses
Title Typ Hrs/wk CP
Approximation and Stability (L0487) Lecture 2 3
Approximation and Stability (L0489) Seminar 1 2
Approximation and Stability (L0488) Recitation Section (small) 1 1
Module Responsible Prof. Marko Lindner
Admission Requirements None
Recommended Previous Knowledge
  • Linear Algebra: systems of linear equations, least squares problems, eigenvalues, singular values
  • Analysis: sequences, series, differentiation, integration
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • sketch and interrelate basic concepts of functional analysis (Hilbert space, operators),
  • name and understand concrete approximation methods,
  • name and explain basic stability theorems,
  • discuss spectral quantities, conditions numbers and methods of regularisation

Skills

Students are able to

  • apply basic results from functional analysis,
  • apply approximation methods,
  • apply stability theorems,
  • compute spectral quantities,
  • apply regularisation methods.
Personal Competence
Social Competence

Students are able to solve specific problems in groups and to present their results appropriately (e.g. as a seminar presentation).

Autonomy
  • Students are capable of checking their understanding of complex concepts on their own. They can specify open questions precisely and know where to get help in solving them.
  • Students have developed sufficient persistence to be able to work for longer periods in a goal-oriented manner on hard problems.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0487: Approximation and Stability
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle SoSe
Content

This course is about solving the following basic problems of Linear Algebra,

  • systems of linear equations,
  • least squares problems,
  • eigenvalue problems

but now in function spaces (i.e. vector spaces of infinite dimension) by a stable approximation of the problem in a space of finite dimension.

Contents:

  • crash course on Hilbert spaces: metric, norm, scalar product, completeness
  • crash course on operators: boundedness, norm, compactness, projections
  • uniform vs. strong convergence, approximation methods
  • applicability and stability of approximation methods, Polski's theorem
  • Galerkin methods, collocation, spline interpolation, truncation
  • convolution and Toeplitz operators
  • crash course on C*-algebras
  • convergence of condition numbers
  • convergence of spectral quantities: spectrum, eigen values, singular values, pseudospectra
  • regularisation methods (truncated SVD, Tichonov)
Literature
  • R. Hagen, S. Roch, B. Silbermann: C*-Algebras in Numerical Analysis
  • H. W. Alt: Lineare Funktionalanalysis
  • M. Lindner: Infinite matrices and their finite sections
Course L0489: Approximation and Stability
Typ Seminar
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course
Course L0488: Approximation and Stability
Typ Recitation Section (small)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Marko Lindner
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0835: Humanoid Robotics

Courses
Title Typ Hrs/wk CP
Humanoid Robotics (L0663) Seminar 2 2
Module Responsible Prof. Herbert Werner
Admission Requirements None
Recommended Previous Knowledge


  • Introduction to control systems
  • Control theory and design
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain humanoid robots.
  • Students learn to apply basic control concepts for different tasks in humanoid robotics.

Skills
  • Students acquire knowledge about selected aspects of humanoid robotics, based on specified literature
  • Students generalize developed results and present them to the participants
  • Students practice to prepare and give a presentation
Personal Competence
Social Competence
  • Students are capable of developing solutions in interdisciplinary teams and present them
  • They are able to provide appropriate feedback and handle constructive criticism of their own results
Autonomy
  • Students evaluate advantages and drawbacks of different forms of presentation for specific tasks and select the best solution
  • Students familiarize themselves with a scientific field, are able of introduce it and follow presentations of other students, such that a scientific discussion develops
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Presentation
Examination duration and scale 30 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0663: Humanoid Robotics
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language DE
Cycle SoSe
Content
  • Grundlagen der Regelungstechnik
  • Control systems theory and design

Literature

- B. Siciliano, O. Khatib. "Handbook of Robotics. Part A: Robotics Foundations",

Springer (2008).


Module M0714: Numerical Treatment of Ordinary Differential Equations

Courses
Title Typ Hrs/wk CP
Numerical Treatment of Ordinary Differential Equations (L0576) Lecture 2 3
Numerical Treatment of Ordinary Differential Equations (L0582) Recitation Section (small) 2 3
Module Responsible Prof. Blanca Ayuso Dios
Admission Requirements None
Recommended Previous Knowledge
  • Mathematik I, II, III für Ingenieurstudierende (deutsch oder englisch) oder Analysis & Lineare Algebra I + II sowie Analysis III für Technomathematiker
  • Basic MATLAB knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to

  • list numerical methods for the solution of ordinary differential equations and explain their core ideas,
  • repeat convergence statements for the treated numerical methods (including the prerequisites tied to the underlying problem),
  • explain aspects regarding the practical execution of a method.
Skills

Students are able to

  • implement (MATLAB), apply and compare numerical methods for the solution of ordinary differential equations,
  • to justify the convergence behaviour of numerical methods with respect to the posed problem and selected algorithm,
  • for a given problem, develop a suitable solution approach, if necessary by the composition of several algorithms, to execute this approach and to critically evaluate the results.


Personal Competence
Social Competence

Students are able to

  • work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge), explain theoretical foundations and support each other with practical aspects regarding the implementation of algorithms.
Autonomy

Students are capable

  • to assess whether the supporting theoretical and practical excercises are better solved individually or in a team,
  • to assess their individual progess and, if necessary, to ask questions and seek help.
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 180 min
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation General Process Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Energy Systems: Core qualification: Elective Compulsory
Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Technomathematics: Specialisation I. Mathematics: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Compulsory
Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Course L0576: Numerical Treatment of Ordinary Differential Equations
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Patricio Farrell
Language DE/EN
Cycle SoSe
Content

Numerical methods for Initial Value Problems

  • single step methods
  • multistep methods
  • stiff problems
  • differential algebraic equations (DAE) of index 1

Numerical methods for Boundary Value Problems

  • initial value methods
  • multiple shooting method
  • difference methods
  • variational methods


Literature
  • E. Hairer, S. Noersett, G. Wanner: Solving Ordinary Differential Equations I: Nonstiff Problems
  • E. Hairer, G. Wanner: Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems
Course L0582: Numerical Treatment of Ordinary Differential Equations
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Dr. Patricio Farrell
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0838: Linear and Nonlinear System Identifikation

Courses
Title Typ Hrs/wk CP
Linear and Nonlinear System Identification (L0660) Lecture 2 3
Module Responsible Prof. Herbert Werner
Admission Requirements Control Systems Theory and Design
Recommended Previous Knowledge
  • Classical control (frequency response, root locus)
  • State space methods
  • Discrete-time systems
  • Linear algebra, singular value decomposition
  • Basic knowledge about stochastic processes
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the general framework of the prediction error method and its application to a variety of linear and nonlinear model structures
  • They can explain how multilayer perceptron networks are used to model nonlinear dynamics
  • They can explain how an approximate predictive control scheme can be based on neural network models
  • They can explain the idea of subspace identification and its relation to Kalman realisation theory
Skills
  • Students are capable of applying the predicition error method to the experimental identification of linear and nonlinear models for dynamic systems
  • They are capable of implementing a nonlinear predictive control scheme based on a neural network model
  • They are capable of applying subspace algorithms to the experimental identification of linear models for dynamic systems
  • They can do the above using standard software tools (including the Matlab System Identification Toolbox)
Personal Competence
Social Competence

Students can work in mixed groups on specific problems to arrive at joint solutions. 

Autonomy

Students are able to find required information in sources provided (lecture notes, literature, software documentation) and use it to solve given problems. 

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0660: Linear and Nonlinear System Identification
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle SoSe
Content
  • Prediction error method
  • Linear and nonlinear model structures
  • Nonlinear model structure based on multilayer perceptron network
  • Approximate predictive control based on multilayer perceptron network model
  • Subspace identification
Literature
  • Lennart Ljung, System Identification - Theory for the User, Prentice Hall 1999
  • M. Norgaard, O. Ravn, N.K. Poulsen and L.K. Hansen, Neural Networks for Modeling and Control of Dynamic Systems, Springer Verlag, London 2003
  • T. Kailath, A.H. Sayed and B. Hassibi, Linear Estimation, Prentice Hall 2000

Module M0845: Feedback Control in Medical Technology

Courses
Title Typ Hrs/wk CP
Feedback Control in Medical Technology (L0664) Lecture 2 3
Module Responsible Prof. Olaf Simanski
Admission Requirements
Recommended Previous Knowledge

Basics in Control, Basics in Physiology

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The lecture will introduce into the fascinating area of medical technology with the engineering point of view. Fundamentals in human physiology will be similarly introduced like knowledge in control theory.

Internal control loops of the human body will be discussed in the same way like the design of external closed loop system fo example in for anesthesia control.

The handling of PID controllers and modern controller like predictive controller or fuzzy controller or neural networks will be illustrated. The operation of simple equivalent circuits will be discussed.

Skills

Application of modeling, identification, control technology in the field of medical technology.


Personal Competence
Social Competence

Students can develop solutions to specific problems in small groups and present their results (e.g. during project week)

Autonomy

Students are able to find necessary literature and to set it into the context of the lecture. They are able to continuously evaluate their knowledge and to take control of their learning process. They can combine knowledge from different courses to form a consistent whole.

Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Credit points 3
Examination Oral exam
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Medical Technology: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Course L0664: Feedback Control in Medical Technology
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Ulf Pilz, Prof. Olaf Simanski
Language DE
Cycle SoSe
Content

Taking an engineering point of view, the lecture is structured as follows.

  • Introduction to the topic with selected examples
  • Physiology - introduction and overview
  • Regeneration of functions of the cardiovascular system
  • Regeneration of the respiratory functions
  • Closed loop control in anesthesia
  • regeneration of kidney and liver functions
  • regeneration of motorize function/ rehabilitation engineering 
  • navigation systems and robotic in medicine

 The lecture will use knowledge from modeling, simulation and controller design and MATLAB and SIMULINK will be used.


Literature

Silbernagel/Depopoulos: Taschenatlas der Physiologie, Thieme Verlag Stuttgart

Werner: Kooperative und autonome Systeme der Medizintechnik, Oldenburg Verlag

M.C.K.Khoo:“Physiological Control System“, IEEE Press, 2000

Module M0932: Process Measurement Engineering

Courses
Title Typ Hrs/wk CP
Process Measurement Engineering (L1077) Lecture 2 3
Process Measurement Engineering (L1083) Recitation Section (large) 1 1
Module Responsible Prof. Roland Harig
Admission Requirements

Bachelor in Elektrotechnik or Mechatronik


Recommended Previous Knowledge

Fundamental principles of electrical engineering and measurement technology


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students possess an understanding of complex, state-of-the-art process measurement equipment. They can relate devices and procedures to a variety of commonly used measurement and communications technology.


Skills

The students are capable of modeling and evaluating complex systems of sensing devices as well as associated communications systems. An emphasis is placed on a system-oriented understanding of the measurement equipment.




Personal Competence
Social Competence

Students can communicate the discussed technologies using the English language.


Autonomy

Students are capable of gathering necessary information from provided references and relate this information to the lecture. They are able to continually reflect their knowledge by means of activities that accompany the lecture. Based on respective feedback, students are expected to adjust their individual learning process. They are able to draw connections between their knowledge obtained in this lecture and the content of other lectures (e.g. Fundamentals of Electrical Engineering, Analysis, Stochastic Processes, Communication Systems).


Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Oral exam
Examination duration and scale 45 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Course L1077: Process Measurement Engineering
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Roland Harig
Language DE/EN
Cycle SoSe
Content
  • Process measurement engineering in the context of process control engineering
    • Challenges of process measurement engineering
    • Instrumentation of processes
    • Classification of pickups
  • Systems theory in process measurement engineering
    • Generic linear description of pickups
    • Mathematical description of two-port systems
    • Fourier and Laplace transformation
  • Correlational measurement
    • Wide band signals
    • Auto- and cross-correlation function and their applications
    • Fault-free operation of correlational methods
  • Transmission of analog and digital measurement signals
    • Modulation process (amplitude and frequency modulation)
    • Multiplexing
    • Analog to digital converter


Literature

- Färber: „Prozeßrechentechnik“, Springer-Verlag 1994

- Kiencke, Kronmüller: „Meßtechnik“, Springer Verlag Berlin Heidelberg, 1995

- A. Ambardar: „Analog and Digital Signal Processing“ (1), PWS Publishing Company, 1995, NTC 339

- A. Papoulis: „Signal Analysis“ (1), McGraw-Hill, 1987, NTC 312 (LB)

- M. Schwartz: „Information Transmission, Modulation and Noise“ (3,4), McGraw-Hill, 1980, 2402095

- S. Haykin: „Communication Systems“ (1,3), Wiley&Sons, 1983, 2419072

- H. Sheingold: „Analog-Digital Conversion Handbook“ (5), Prentice-Hall, 1986, 2440072

- J. Fraden: „AIP Handbook of Modern Sensors“ (5,6), American Institute of Physics, 1993, MTB 346


Course L1083: Process Measurement Engineering
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Roland Harig
Language DE/EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0935: Microcontroller Circuits: Implementation in Hardware and Software

Courses
Title Typ Hrs/wk CP
Microcontroller Circuits: Implementation in Hardware and Software (L0087) Seminar 2 2
Module Responsible Prof. Siegfried Rump
Admission Requirements none.
Recommended Previous Knowledge lecture: Computer Architectures
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students can describe parts and operation of a common family of microcontrollers. They know details about operations of CPUs, and they can transfer algorithms to machine code.
Skills

The students can design and use electronic circuits (digital with some analogue parts). Furthermore they are able to implement solutions of some tasks by way of assembler programming on these circuits.

Personal Competence
Social Competence

Groups of two students work on special projects. The students have the skill to separate the project into smaller parts and to present the achieved results in an appropriate short talk.

Autonomy The student can use, select and estimate suitable sources, which are available from information technology companies. They apply those findings to their projects.
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Written elaboration
Examination duration and scale 15 minutes + disputation
Assignment for the Following Curricula Electrical Engineering: Specialisation Nanoelectronics and Microsystems Technology: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory
Course L0087: Microcontroller Circuits: Implementation in Hardware and Software
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Siegfried Rump
Language DE
Cycle WiSe/SoSe
Content
Literature

Module M0939: Control Lab A

Courses
Title Typ Hrs/wk CP
Control Lab I (L1093) Laboratory Course 1 1
Control Lab II (L1291) Laboratory Course 1 1
Control Lab III (L1665) Laboratory Course 1 1
Control Lab IV (L1666) Laboratory Course 1 1
Module Responsible Prof. Herbert Werner
Admission Requirements

Recommended Previous Knowledge
  • State space methods
  • LQG control
  • H2 and H-infinity optimal control
  • uncertain plant models and robust control
  •  LPV control
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the difference between validation of a control lop in simulation and experimental validation

Skills
  • Students are capable of applying basic system identification tools (Matlab System Identification Toolbox) to identify a dynamic model that can be used for controller synthesis
  • They are capable of using standard software tools (Matlab Control Toolbox) for the design and implementation of LQG controllers
  • They are capable of using standard software tools (Matlab Robust Control Toolbox) for the mixed-sensitivity design and the implementation of H-infinity optimal controllers
  • They are capable of representing model uncertainty, and of designing and implementing a robust controller
  • They are capable of using standard software tools (Matlab Robust Control Toolbox) for the design and the implementation of LPV gain-scheduled controllers
Personal Competence
Social Competence
  • Students can work in teams to conduct experiments and document the results
Autonomy
  • Students can independently carry out simulation studies to design and validate control loops
Workload in Hours Independent Study Time 64, Study Time in Lecture 56
Credit points 4
Examination Colloquium
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L1093: Control Lab I
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Herbert Werner, Antonio Mendez Gonzalez
Language EN
Cycle WiSe/SoSe
Content One of the offered experiments in control theory.
Literature

Experiment Guides


Course L1291: Control Lab II
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Herbert Werner, Antonio Mendez Gonzalez
Language EN
Cycle WiSe/SoSe
Content One of the offered experiments in control theory.
Literature

Experiment Guides

Course L1665: Control Lab III
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Herbert Werner, Antonio Mendez Gonzalez
Language EN
Cycle WiSe/SoSe
Content One of the offered experiments in control theory.
Literature

Experiment Guides

Course L1666: Control Lab IV
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Herbert Werner, Antonio Mendez Gonzalez
Language EN
Cycle WiSe/SoSe
Content One of the offered experiments in control theory.
Literature

Experiment Guides

Module M0840: Optimal and Robust Control

Courses
Title Typ Hrs/wk CP
Optimal and Robust Control (L0658) Lecture 2 3
Optimal and Robust Control (L0659) Recitation Section (small) 2 3
Module Responsible Prof. Herbert Werner
Admission Requirements

Control Systems Theory and Design

Recommended Previous Knowledge
  • Classical control (frequency response, root locus)
  • State space methods
  • Linear algebra, singular value decomposition
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the significance of the matrix Riccati equation for the solution of LQ problems.
  • They can explain the duality between optimal state feedback and optimal state estimation.
  • They can explain how the H2 and H-infinity norms are used to represent stability and performance constraints.
  • They can explain how an LQG design problem can be formulated as special case of an H2 design problem.
  • They  can explain how model uncertainty can be represented in a way that lends itself to robust controller design
  • They can explain how - based on the small gain theorem - a robust controller can guarantee stability and performance for an uncertain plant.
  • They understand how analysis and synthesis conditions on feedback loops can be represented as linear matrix inequalities.
Skills
  • Students are capable of designing and tuning LQG controllers for multivariable plant models.
  • They are capable of representing a H2 or H-infinity design problem in the form of a generalized plant, and of using standard software tools for solving it.
  • They are capable of translating time and frequency domain specifications for control loops into constraints on closed-loop sensitivity functions, and of carrying out a mixed-sensitivity design.
  • They are capable of constructing an LFT uncertainty model for an uncertain system, and of designing a mixed-objective robust controller.
  • They are capable of formulating analysis and synthesis conditions as linear matrix inequalities (LMI), and of using standard LMI-solvers for solving them.
  • They can carry out all of the above using standard software tools (Matlab robust control toolbox).
Personal Competence
Social Competence Students can work in small groups on specific problems to arrive at joint solutions. 
Autonomy

Students are able to find required information in sources provided (lecture notes, literature, software documentation) and use it to solve given problems. 


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Energy Systems: Core qualification: Elective Compulsory
Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Product Development, Materials and Production: Specialisation Product Development: Elective Compulsory
Product Development, Materials and Production: Specialisation Production: Elective Compulsory
Product Development, Materials and Production: Specialisation Materials: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0658: Optimal and Robust Control
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle SoSe
Content
  • Optimal regulator problem with finite time horizon, Riccati differential equation
  • Time-varying and steady state solutions, algebraic Riccati equation, Hamiltonian system
  • Kalman’s identity, phase margin of LQR controllers, spectral factorization
  • Optimal state estimation, Kalman filter, LQG control
  • Generalized plant, review of LQG control
  • Signal and system norms, computing H2 and H∞ norms
  • Singular value plots, input and output directions
  • Mixed sensitivity design, H∞ loop shaping, choice of weighting filters
  • Case study: design example flight control
  • Linear matrix inequalities, design specifications as LMI constraints (H2, H∞ and pole region)
  • Controller synthesis by solving LMI problems, multi-objective design
  • Robust control of uncertain systems, small gain theorem, representation of parameter uncertainty
Literature
  • Werner, H., Lecture Notes: "Optimale und Robuste Regelung"
  • Boyd, S., L. El Ghaoui, E. Feron and V. Balakrishnan "Linear Matrix Inequalities in Systems and Control", SIAM, Philadelphia, PA, 1994
  • Skogestad, S. and I. Postlewhaite "Multivariable Feedback Control", John Wiley, Chichester, England, 1996
  • Strang, G. "Linear Algebra and its Applications", Harcourt Brace Jovanovic, Orlando, FA, 1988
  • Zhou, K. and J. Doyle "Essentials of Robust Control", Prentice Hall International, Upper Saddle River, NJ, 1998
Course L0659: Optimal and Robust Control
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M1250: Electrical Power Systems II

Courses
Title Typ Hrs/wk CP
Electrical Power Systems II (L1696) Lecture 2 3
Electrical Power Systems II (L1697) Recitation Section (large) 1 1
Module Responsible Prof. Christian Becker
Admission Requirements none
Recommended Previous Knowledge

Fundamentals of Electrical Engineering,

Electrical Power Systems I

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain in detail and critically evaluate technologies and information systems for operational management of conventional and modern electric power systems as well as methods and algorithms for steady-state network calculation, failure calculation, power system operation and optimization. They are additonally able to apply these methods to real electric power systems. 

Skills

With completion of this module the students are able to apply the acquired skills for planning and analysis of real electric power systems and to critically evaluate the results.

Personal Competence
Social Competence

The students can participate in specialized and interdisciplinary discussions, advance ideas and represent their own work results in front of others.

Autonomy

Students can independently tap knowledge of the emphasis of the lectures and apply it within further research activities. 

Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Oral exam
Examination duration and scale 30 - 60 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Course L1696: Electrical Power Systems II
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Christian Becker
Language DE
Cycle SoSe
Content
  • introduction into information and communication technology of electric power systems 
  • steady-state load flow calculation
  • sensitivity analysis
  • short-circuit calculation
  • state estimation
  • power system management
  • optimizing power system operations
  • information systems for power system management
  • architectures of bay-, substation and network control level 
  • protection systems
  • IT integration (energy market / supply shortfall management / asset management)
  • future trends of process control technology
  • smart grids
Literature

E. Handschin: Elektrische Energieübertragungssysteme, Hüthig Verlag

B. R. Oswald: Berechnung von Drehstromnetzen, Springer-Vieweg Verlag

V. Crastan: Elektrische Energieversorgung Bd. 1 & 3, Springer Verlag

E.-G. Tietze: Netzleittechnik Bd. 1 & 2, VDE-Verlag

Course L1697: Electrical Power Systems II
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Christian Becker
Language DE
Cycle SoSe
Content See interlocking course
Literature See interlocking course

Module M0633: Industrial Process Automation

Courses
Title Typ Hrs/wk CP
Industrial Process Automation (L0344) Lecture 2 3
Industrial Process Automation (L0345) Recitation Section (small) 2 3
Module Responsible Prof. Alexander Schlaefer
Admission Requirements None
Recommended Previous Knowledge

mathematics and optimization methods
principles of automata 
principles of algorithms and data structures
programming skills

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

The students can evaluate and assess disctrete event systems. They can evaluate properties of processes and explain methods for process analysis. The students can compare methods for process modelling and select an appropriate method for actual problems. They can discuss scheduling methods in the context of actual problems and give a detailed explanation of advantages and disadvantages of different programming methods.


Skills

The students are able to develop and model processes and evaluate them accordingly. This involves taking into account optimal scheduling, understanding algorithmic complexity and implementation using PLCs.

Personal Competence
Social Competence

The students work in teams to solve problems.


Autonomy

The students can reflect their knowledge and document the results of their work. 


Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 90 minutes
Assignment for the Following Curricula Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Chemical and Bioprocess Engineering: Specialisation General Process Engineering: Elective Compulsory
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Aircraft Systems Engineering: Specialisation Cabin Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
International Production Management: Specialisation Production Technology: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory
Process Engineering: Specialisation Process Engineering: Elective Compulsory
Course L0344: Industrial Process Automation
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content

- foundations of problem solving and system modeling, discrete event systems
- properties of processes, modeling using automata and Petri-nets
- design considerations for processes (mutex, deadlock avoidance, liveness)
- optimal scheduling for processes
- optimal decisions when planning manufacturing systems, decisions under uncertainty
- software design and software architectures for automation, PLCs

Literature

J. Lunze: „Automatisierungstechnik“, Oldenbourg Verlag, 2012
Reisig: Petrinetze: Modellierungstechnik, Analysemethoden, Fallstudien; Vieweg+Teubner 2010
Hrúz, Zhou: Modeling and Control of Discrete-event Dynamic Systems; Springer 2007
Li, Zhou: Deadlock Resolution in Automated Manufacturing Systems, Springer 2009
Pinedo: Planning and Scheduling in Manufacturing and Services, Springer 2009

Course L0345: Industrial Process Automation
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Alexander Schlaefer
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0794: Research Project in Control and Power Systems

Courses
Title Typ Hrs/wk CP
Module Responsible Dozenten des SD E
Admission Requirements None
Recommended Previous Knowledge

Advanced state of knowledge in the electrical engineering master program


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students know current research topics oft institutes engaged in their specialization. They can name the fundamental scientific methods used for doing related reserach.


Skills

Students are capable of completing a small, independent sub-project of currently ongoing research projects in the institutes engaged in their specialization. Students can justify and explain their approach for problem solving, they can draw conclusions from their results, and then can find new ways and methods for their work. Students are capable of comparing and assessing alterantive approaches with their own with regard to given criteria.


Personal Competence
Social Competence

Students are able to discuss their work progress with research assistants of the supervising institute .  They are capable of presenting their results in front of a professional audience.


Autonomy

Based on their competences gained so far students are capable of defining meaningful tasks within ongoing research project for themselves. They are able to develop the necessary understanding  and problem solving methods.


Workload in Hours Independent Study Time 180, Study Time in Lecture 0
Credit points 6
Examination Project (accord. to Subject Specific Regulations)
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory

Module M0677: Digital Signal Processing and Digital Filters

Courses
Title Typ Hrs/wk CP
Digital Signal Processing and Digital Filters (L0446) Lecture 3 4
Digital Signal Processing and Digital Filters (L0447) Recitation Section (large) 1 2
Module Responsible Prof. Gerhard Bauch
Admission Requirements None
Recommended Previous Knowledge
  • Mathematics 1-3
  • Signals and Systems
  • Fundamentals of signal and system theory as well as random processes.
  • Fundamentals of spectral transforms (Fourier series, Fourier transform, Laplace transform)
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge The students know and understand basic algorithms of digital signal processing. They are familiar with the spectral transforms of discrete-time signals and are able to describe and analyse signals and systems in time and image domain. They know basic structures of digital filters and can identify and assess important properties including stability. They are aware of the effects caused by quantization of filter coefficients and signals. They are familiar with the basics of adaptive filters. They can perform traditional and parametric methods of spectrum estimation, also taking a limited observation window into account.
Skills The students are able to apply methods of digital signal processing to new problems. They can choose and parameterize suitable filter striuctures. In particular, the can design adaptive filters according to the minimum mean squared error (MMSE) criterion and develop an efficient implementation, e.g. based on the LMS or RLS algorithm.  Furthermore, the students are able to apply methods of spectrum estimation and to take the effects of a limited observation window into account.
Personal Competence
Social Competence

The students can jointly solve specific problems.

Autonomy

The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system.

Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Written exam
Examination duration and scale 90 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory
Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Microelectronics and Microsystems: Specialisation Microelectronics Complements: Elective Compulsory
Course L0446: Digital Signal Processing and Digital Filters
Typ Lecture
Hrs/wk 3
CP 4
Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Lecturer Prof. Gerhard Bauch
Language EN
Cycle WiSe
Content
  • Transforms of discrete-time signals:

    • Discrete-time Fourier Transform (DTFT)

    • Discrete Fourier-Transform (DFT), Fast Fourier Transform (FFT)

    • Z-Transform

  • Correspondence of continuous-time and discrete-time signals, sampling, sampling theorem

  • Fast convolution, Overlap-Add-Method, Overlap-Save-Method

  • Fundamental structures and basic types of digital filters

  • Characterization of digital filters using pole-zero plots, important properties of digital filters

  • Quantization effects

  • Design of linear-phase filters

  • Fundamentals of stochastic signal processing and adaptive filters

    • MMSE criterion

    • Wiener Filter

    • LMS- and RLS-algorithm

  • Traditional and parametric methods of spectrum estimation

Literature

K.-D. Kammeyer, K. Kroschel: Digitale Signalverarbeitung. Vieweg Teubner.

V. Oppenheim, R. W. Schafer, J. R. Buck: Zeitdiskrete Signalverarbeitung. Pearson StudiumA. V.

W. Hess: Digitale Filter. Teubner.

Oppenheim, R. W. Schafer: Digital signal processing. Prentice Hall.

S. Haykin:  Adaptive flter theory.

L. B. Jackson: Digital filters and signal processing. Kluwer.

T.W. Parks, C.S. Burrus: Digital filter design. Wiley.

Course L0447: Digital Signal Processing and Digital Filters
Typ Recitation Section (large)
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Prof. Gerhard Bauch
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M0836: Communication Networks I - Analysis and Structure

Courses
Title Typ Hrs/wk CP
Analysis and Structure of Communication Networks (L0897) Lecture 2 2
Selected Topics of Communication Networks (L0899) Problem-based Learning 2 2
Communication Networks Excercise (L0898) Problem-based Learning 1 2
Module Responsible Prof. Andreas Timm-Giel
Admission Requirements None
Recommended Previous Knowledge
  • Fundamental stochastics
  • Basic understanding of computer networks and/or communication technologies is beneficial
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to describe the principles and structures of communication networks in detail. They can explain the formal description methods of communication networks and their protocols. They are able to explain how current and complex communication networks work and describe the current research in these examples.

Skills

Students are able to evaluate the performance of communication networks using the learned methods. They are able to work out problems themselves and apply the learned methods. They can apply what they have learned autonomously on further and new communication networks.

Personal Competence
Social Competence

Students are able to define tasks themselves in small teams and solve these problems together using the learned methods. They can present the obtained results. They are able to discuss and critically analyse the solutions.

Autonomy

Students are able to obtain the necessary expert knowledge for understanding the functionality and performance capabilities of new communication networks independently.

Workload in Hours Independent Study Time 110, Study Time in Lecture 70
Credit points 6
Examination Colloquium
Examination duration and scale 1.5 hours colloquium with three students, therefore about 30 min per student. Topics of the colloquium are the posters from the previous poster session and the topics of the module.
Assignment for the Following Curricula Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory
Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory
Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory
Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory
Mechatronics: Technical Complementary Course: Elective Compulsory
Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory
Course L0897: Analysis and Structure of Communication Networks
Typ Lecture
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Andreas Timm-Giel
Language EN
Cycle WiSe
Content
Literature
  • Skript des Instituts für Kommunikationsnetze
  • Tannenbaum, Computernetzwerke, Pearson-Studium


Further literature is announced at the beginning of the lecture.

Course L0899: Selected Topics of Communication Networks
Typ Problem-based Learning
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Dr. Maciej Mühleisen
Language EN
Cycle WiSe
Content Example networks selected by the students will be researched on in a PBL course by the students in groups and will be presented in a poster session at the end of the term.
Literature
  • see lecture
Course L0898: Communication Networks Excercise
Typ Problem-based Learning
Hrs/wk 1
CP 2
Workload in Hours Independent Study Time 46, Study Time in Lecture 14
Lecturer Dr. Maciej Mühleisen
Language EN
Cycle WiSe
Content Part of the content of the lecture Communication Networks are reflected in computing tasks in groups, others are motivated and addressed in the form of a PBL exercise.
Literature
  • announced during lecture

Module M1229: Control Lab B

Courses
Title Typ Hrs/wk CP
Control Lab V (L1667) Laboratory Course 1 1
Control Lab VI (L1668) Laboratory Course 1 1
Module Responsible Prof. Herbert Werner
Admission Requirements None
Recommended Previous Knowledge
  • State space methods
  • LQG control
  • H2 and H-infinity optimal control
  • uncertain plant models and robust control
  •  LPV control
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the difference between validation of a control lop in simulation and experimental validation
Skills
  • Students are capable of applying basic system identification tools (Matlab System Identification Toolbox) to identify a dynamic model that can be used for controller synthesis
  • They are capable of using standard software tools (Matlab Control Toolbox) for the design and implementation of LQG controllers
  • They are capable of using standard software tools (Matlab Robust Control Toolbox) for the mixed-sensitivity design and the implementation of H-infinity optimal controllers
  • They are capable of representing model uncertainty, and of designing and implementing a robust controller
  • They are capable of using standard software tools (Matlab Robust Control Toolbox) for the design and the implementation of LPV gain-scheduled controllers
Personal Competence
Social Competence
  • Students can work in teams to conduct experiments and document the results
Autonomy
  • Students can independently carry out simulation studies to design and validate control loops
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Colloquium
Examination duration and scale
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L1667: Control Lab V
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Herbert Werner, Antonio Mendez Gonzalez
Language EN
Cycle WiSe/SoSe
Content One of the offered experiments in control theory.
Literature

Experiment Guides

Course L1668: Control Lab VI
Typ Laboratory Course
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Herbert Werner, Antonio Mendez Gonzalez
Language EN
Cycle WiSe/SoSe
Content One of the offered experiments in control theory.
Literature

Experiment Guides

Module M1236: Electrical Power Systems III

Courses
Title Typ Hrs/wk CP
Electrical Power Systems III (L1683) Lecture 2 3
Electrical Power Systems III (L1684) Recitation Section (large) 1 1
Module Responsible Prof. Christian Becker
Admission Requirements None
Recommended Previous Knowledge

Fundamentals of Electrical Engineering,

Introduction to Control Systems,

Electrical Power Systems I

Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students are able to explain in detail and critically evaluate methods for modelling, control and stability analyses of electric power systems. 

Skills

With completion of this module the students are able to calculate and analyze the dynamic bahaviour and stability of real electric power systems using appropriate models. They are furthermore able to design voltage and load frequency controllers.

Personal Competence
Social Competence

The students can participate in specialized and interdisciplinary discussions, advance ideas and represent their own work results in front of others.

Autonomy

Students can independently tap knowledge of the emphasis of the lectures and apply it within further research activities. 

Workload in Hours Independent Study Time 78, Study Time in Lecture 42
Credit points 4
Examination Oral exam
Examination duration and scale 30 - 60 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Course L1683: Electrical Power Systems III
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Christian Becker
Language DE
Cycle WiSe/SoSe
Content
  • power system dynamics
  • power plant and turbine modelling
  • load-frequency control
  • energy exchange
  • synchronous machine modelling
  • direct-quadrature-zero transformation
  • small-signal stability
  • voltage stability, voltage control
  • Flexible AC Transmission Systems (FACTS), influence of FACTS on power system stability
Literature

E. Handschin: Elektrische Energieübertragungssysteme, Hüthig Verlag

P. Kundur: Power System Stability and Control, McGraw-Hill, 1994

Course L1684: Electrical Power Systems III
Typ Recitation Section (large)
Hrs/wk 1
CP 1
Workload in Hours Independent Study Time 16, Study Time in Lecture 14
Lecturer Prof. Christian Becker
Language DE
Cycle WiSe/SoSe
Content See interlocking course
Literature See interlocking course

Module M0832: Advanced Topics in Control

Courses
Title Typ Hrs/wk CP
Advanced Topics in Control (L0661) Lecture 2 3
Advanced Topics in Control (L0662) Recitation Section (small) 2 3
Module Responsible Prof. Herbert Werner
Admission Requirements None
Recommended Previous Knowledge H-infinity optimal control, mixed-sensitivity design, linear matrix inequalities 
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain the advantages and shortcomings of the classical gain scheduling approach
  • They can explain the representation of nonlinear systems in the form of quasi-LPV systems
  • They can explain how stability and performance conditions for LPV systems can be formulated as LMI conditions
  • They can explain how gridding techniques can be used to solve analysis and synthesis problems for LPV systems
  • They are familiar with polytopic and LFT representations of LPV systems and some of the basic synthesis techniques associated with each of these model structures


  • Students can explain how graph theoretic concepts are used to represent the communication topology of multiagent systems
  • They can explain the convergence properties of  first order consensus protocols
  • They can explain analysis and synthesis conditions for formation control loops involving either LTI or LPV agent models


  • Students can explain the state space representation of spatially invariant distributed systems that are discretized according to an actuator/sensor array
  • They can explain (in outline) the extension of the bounded real lemma to such distributed systems and the associated synthesis conditions for distributed controllers

Skills
  • Students are capable of constructing LPV models of nonlinear plants and carry out a mixed-sensitivity design of gain-scheduled controllers; they can do this using polytopic, LFT or general LPV models 
  • They are able to use standard software tools (Matlab robust control toolbox) for these tasks


  • Students are able to design distributed formation controllers for groups of agents with either LTI or LPV dynamics, using Matlab tools provided


  • Students are able to design distributed controllers for spatially interconnected systems, using the Matlab MD-toolbox
Personal Competence
Social Competence Students can work in small groups and arrive at joint results.
Autonomy

Students are able to find required information in sources provided (lecture notes, literature, software documentation) and use it to solve given problems. 


 
Workload in Hours Independent Study Time 124, Study Time in Lecture 56
Credit points 6
Examination Oral exam
Examination duration and scale 30 min
Assignment for the Following Curricula Computer Science: Specialisation Intelligence Engineering: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory
Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory
International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory
Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory
Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory
Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory
Theoretical Mechanical Engineering: Core qualification: Elective Compulsory
Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory
Course L0661: Advanced Topics in Control
Typ Lecture
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle WiSe
Content
  • Linear Parameter-Varying (LPV) Gain Scheduling

    - Linearizing gain scheduling, hidden coupling
    - Jacobian linearization vs. quasi-LPV models
    - Stability and induced L2 norm of LPV systems
    - Synthesis of LPV controllers based on the two-sided projection lemma
    - Simplifications: controller synthesis for polytopic and LFT models
    - Experimental identification of LPV models
    - Controller synthesis based on input/output models
    - Applications: LPV torque vectoring for electric vehicles, LPV control of a robotic manipulator
  • Control of Multi-Agent Systems

    - Communication graphs
    - Spectral properties of the graph Laplacian
    - First and second order consensus protocols
    - Formation control, stability and performance
    - LPV models for agents subject to nonholonomic constraints
    - Application: formation control for a team of quadrotor helicopters
  • Control of Spatially Interconnected Systems

    - Multidimensional signals, l2 and L2 signal norm
    - Multidimensional systems in Roesser state space form
    - Extension of real-bounded lemma to spatially interconnected systems
    - LMI-based synthesis of distributed controllers
    - Spatial LPV control of spatially varying systems
    - Applications: control of temperature profiles, vibration damping for an actuated beam
Literature
  • Werner, H., Lecture Notes "Advanced Topics in Control"
  • Selection of relevant research papers made available as pdf documents via StudIP
Course L0662: Advanced Topics in Control
Typ Recitation Section (small)
Hrs/wk 2
CP 3
Workload in Hours Independent Study Time 62, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle WiSe
Content See interlocking course
Literature See interlocking course

Module M1305: Seminar Advanced Topics in Control

Courses
Title Typ Hrs/wk CP
Advanced Topics in Control (L1803) Seminar 2 2
Module Responsible Prof. Herbert Werner
Admission Requirements None
Recommended Previous Knowledge
  • Introduction to control systems
  • Control theory and design
  • optimal and robust control
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • Students can explain modern control.
  • Students learn to apply basic control concepts for different tasks
Skills
  • Students acquire knowledge about selected aspects of modern control, based on specified literature
  • Students generalize developed results and present them to the participants
  • Students practice to prepare and give a presentation
Personal Competence
Social Competence
  • Students are capable of developing solutions and present them
  • They are able to provide appropriate feedback and handle constructive criticism of their own results
Autonomy
  • Students evaluate advantages and drawbacks of different forms of presentation for specific tasks and select the best solution
  • Students familiarize themselves with a scientific field, are able of introduce it and follow presentations of other students, such that a scientific discussion develops
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Presentation
Examination duration and scale 90 min
Assignment for the Following Curricula Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Mechatronics: Specialisation System Design: Elective Compulsory
Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory
Course L1803: Advanced Topics in Control
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Herbert Werner
Language EN
Cycle WiSe/SoSe
Content
  • Seminar on selected topics in modern control
Literature
  • To be specified

Module M0666: Seminar on Electromagnetic Compatibility and Electrical Power Systems

Courses
Title Typ Hrs/wk CP
Seminar on Electromagnetic Compatibility and Electrical Power Systems (L0409) Seminar 2 2
Module Responsible Prof. Christian Schuster
Admission Requirements None
Recommended Previous Knowledge

Fundamentals of electrical engineering


Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge

Students know current research topics in the fields of electromagnetic compatibility, theory of electromagnetic fields, and electrical power systems. They are able to use professional language in discussions. They are able to explain research topics.


Skills

Students are able to gain knowledge about a new field by themselves. In order to do that they make use of their existing knowledge and try to connect it with the topics of the new field. They close their knowledge gaps by discussing with research assistants and by their own literature and internet search. They are capable of summarizing and presenting scientific publications.  


Personal Competence
Social Competence

In cooperation with research assistants students are able to familiarize themselves with and discuss with others current research topics. They are capable of drafting, presenting, and explaining summaries of these topics in English in front of a professional audience.


Autonomy

Students are capable of gathering information from subject related, professional publications and relate that information to the context of the seminar. They are able to find on their own new sources in the Internet. They are able to make a connection with the subject of their chosen specialization.


Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Credit points 2
Examination Presentation
Examination duration and scale 20-30 minutes
Assignment for the Following Curricula Electrical Engineering: Specialisation Microwave Engineering, Optics, and Electromagnetic Compatibility: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Electrical Engineering: Specialisation Control and Power Systems: Elective Compulsory
Course L0409: Seminar on Electromagnetic Compatibility and Electrical Power Systems
Typ Seminar
Hrs/wk 2
CP 2
Workload in Hours Independent Study Time 32, Study Time in Lecture 28
Lecturer Prof. Christian Schuster, Prof. Frank Gronwald, Prof. Christian Becker
Language EN
Cycle WiSe/SoSe
Content

Current research topics in the fields electromagnetic compatibility, theory of electromagnetic fields, and electrical power systems




Literature

Aktuelle Literatur zu Forschungsthemen aus der elektromagnetischen Verträglichkeit, der theoretischen Elektrotechnik und der elektrischen Energiesystemtechnik / Current literature with regard to research topics in the fields of electromagnetic compatibility, theory of electromagnetic fields, and and electrical power systems







Thesis

Module M-002: Master Thesis

Courses
Title Typ Hrs/wk CP
Module Responsible Professoren der TUHH
Admission Requirements
  • According to General Regulations §24 (1):

    At least 78 credit points have to be achieved in study programme. The examinations board decides on exceptions.

Recommended Previous Knowledge
Educational Objectives After taking part successfully, students have reached the following learning results
Professional Competence
Knowledge
  • The students can use specialized knowledge (facts, theories, and methods) of their subject competently on specialized issues.
  • The students can explain in depth the relevant approaches and terminologies in one or more areas of their subject, describing current developments and taking up a critical position on them.
  • The students can place a research task in their subject area in its context and describe and critically assess the state of research.


Skills

The students are able:

  • To select, apply and, if necessary, develop further methods that are suitable for solving the specialized problem in question.
  • To apply knowledge they have acquired and methods they have learnt in the course of their studies to complex and/or incompletely defined problems in a solution-oriented way.
  • To develop new scientific findings in their subject area and subject them to a critical assessment.
Personal Competence
Social Competence

Students can

  • Both in writing and orally outline a scientific issue for an expert audience accurately, understandably and in a structured way.
  • Deal with issues competently in an expert discussion and answer them in a manner that is appropriate to the addressees while upholding their own assessments and viewpoints convincingly.


Autonomy

Students are able:

  • To structure a project of their own in work packages and to work them off accordingly.
  • To work their way in depth into a largely unknown subject and to access the information required for them to do so.
  • To apply the techniques of scientific work comprehensively in research of their own.
Workload in Hours Independent Study Time 900, Study Time in Lecture 0
Credit points 30
Examination according to Subject Specific Regulations
Examination duration and scale see FSPO
Assignment for the Following Curricula Civil Engineering: Thesis: Compulsory
Bioprocess Engineering: Thesis: Compulsory
Chemical and Bioprocess Engineering: Thesis: Compulsory
Computer Science: Thesis: Compulsory
Electrical Engineering: Thesis: Compulsory
Energy and Environmental Engineering: Thesis: Compulsory
Energy Systems: Thesis: Compulsory
Environmental Engineering: Thesis: Compulsory
Aircraft Systems Engineering: Thesis: Compulsory
Global Innovation Management: Thesis: Compulsory
Computational Science and Engineering: Thesis: Compulsory
Information and Communication Systems: Thesis: Compulsory
International Production Management: Thesis: Compulsory
International Management and Engineering: Thesis: Compulsory
Joint European Master in Environmental Studies - Cities and Sustainability: Thesis: Compulsory
Logistics, Infrastructure and Mobility: Thesis: Compulsory
Materials Science: Thesis: Compulsory
Mechanical Engineering and Management: Thesis: Compulsory
Mechatronics: Thesis: Compulsory
Biomedical Engineering: Thesis: Compulsory
Microelectronics and Microsystems: Thesis: Compulsory
Product Development, Materials and Production: Thesis: Compulsory
Renewable Energies: Thesis: Compulsory
Naval Architecture and Ocean Engineering: Thesis: Compulsory
Ship and Offshore Technology: Thesis: Compulsory
Theoretical Mechanical Engineering: Thesis: Compulsory
Process Engineering: Thesis: Compulsory
Water and Environmental Engineering: Thesis: Compulsory