Electronics Engineering M.Sc. (also available as cooperative degree programme)*

For this placeholder module, students are to select a specific module from the “Electronics Engineering Lab Elect-

ive” Catalogue. For students of non-dual variant, these are currently:

 1.10 Engineering Lab

 1.11 Data Analysis and Visualization

After successful completion of the two modules “Engineering Lab” and “Data Analysis and Visualization” students

have extended and deepened their practical skills and knowledge in Electronics Engineering.

Students of dual variant pick two modules from technical electives catalogue. The individual module choice should

be taken in consideration with the head of the program.

For detailed learning outcomes please see the module descriptions of each elective module.

Course content:

For course contents please see the module descriptions of each elective module.

For this placeholder module, students are to select a specific module from the “Scientific Techniques Elective”

Catalogue. Students of dual variant pick module 1.13 “Efficient Programming”, students of non-dual variant 1.12

“Academic Writing”.

 1.12 Academic Writing

 1.13 Efficient Programming

Learning outcomes:

After completion of the selected Scientific Techniques Elective module, students have extended and deepened

their practical skills in knowledge and application of essential scientific techniques relevant in Electronics Engin-

eering. They are able to apply their knowledge and problem-solving skills in complex contexts within the scope of

the specific module topic.

 Introduction to EEP: Subjects are related to the Electronics Engineering program and

are usually inspired by current research projects in institutes i3m, IWSS and IAT

 Methods on scientific investigations in electronics engineering using literature and

internet support

 Team work

 Project implementation, scheduling, monitoring and control

 Function, performance and application of project relevant engineering components,

design tools and measurement equipment within a defined research project on

optics, electronics, microsystems, communications, measurement and instrumenta-

tion

 Methods on evaluation of results, documentation and presentation techniques

In the dual variants of the program, the Theory-Practice-Project modules 1, 2 and 3 (TPP 1, TPP2 and TPP3) are designed to realize the mutual transfer between the scientific knowledge gained at university and the practical competencies acquired at the cooperating company.

The modules are interconnected, as students conduct an individual industrial project that stretches over two (in the four-semesters program possibly three) semesters, thus preparing them for the master's thesis, which is carried out as a practice project at the cooperating company in the last semester. The specific application reference in the TPP module is influenced by the needs of the respective partner company and is specified in consultation between the university, company and students. TPP module are completed at the two learning locations involved in dual studies, combining project work at the cooperating company with accompanying Academic Project Consulting at HSB.

Students who do not have at least C1 level according to the Common European Framework of Reference for Languages take a German language course. Students with appropriate German language skills take an elective module.

 Concepts of standards in international context

 Statistics, types of error, sources of error,

measurement uncertainty

 Design of experiments

 Static and dynamic behaviour of measuring setup

 Scientific documentation of setup and procedure

 Regression, goodness of fit, global and local

interpolation, spline interpolati

 Scientific documentation of data base and evaluation procedure;

 Quantitative and qualitative information;

 Research and data analysis;

 Principle of design and methodology of data visualization;

 Regression methods, goodness of fit, global and local interpolation, spline interpolation.

 Methods and techniques of scientific writing

 Systematic literature research including scientific databases

 Reviewing state of articulate

 Arguing, correct referencing and citing

 Writing cycle (Drafting-Feedback-Revising)

 Scientific genres: Abstract, expose, report, article, protocol

 Presentation techniques

 Data types, operators, expressions

 Control structures and their description

 Pointers, arrays, strings, memory, structures and unions

 I/O

 Object orientation (classes, objects, data abstraction, methods, reference data types, inheritance,

interfaces, polymorphism),

 Numerical Integration & Differentiation

 Interpolation and Optimization

 Discrete Fourier Transform & Convolution

German courses refer to the Common European Framework of Reference (CEFR); learning outcomes are given here for level A 1:

Can understand and use familiar everyday expressions and very basic phrases aimed at the satisfaction of needs of a concrete type. Can introduce him/herself and others and can ask and answer questions about personal details such as where he/she lives, people he/she knows and things he/she has. Can interact in a simple way provided the other person talks slowly and clearly and is prepared to help.

For this placeholder module, students are to select a specific module from the “Technical Electives Catalogue”. The program can be studied with a study profile in either “Development and Fabrication of Intelligent Systems” or “Application of Intelligent systems”, if they complete at least four technical elective modules assigned to one pro-file and write their Master’s thesis in a field matching the same profile. The respective study profile will be specified in the graduation certificate. For each Technical Elective it is marked in the module description which profile(es) (one or both) it is assigned to.

 Analyzing and simulating mixed-technology systems over all physical domains,

 Design mixed-technology-systems on printed-circuit board (PCB) and integrated-circuit (IC) level,

 Interfacing and aggregating mixed-technology systems.

 Typical working principles of optical and photonic systems

 Construction of rays passing through an optical system

 Characterization of optical systems

 Numerical beam propagation with Python

 Development of beam delivery and beam shaping systems

 Application of geometrical and wave optical principles for system design

 Optical metrology and spectroscopy

 Fourier optics

 Basics of numerical programming and vectorized calculation

 Numerical Integration & Differentiation

 Solving LSE & non-linear SE

 Interpolation

 Optimization

 Discrete Fourier Transform & Convolution

 Systems Thinking and Complexity

 Systems Life Cycle and Engineering Processes

 Requirement Engineering

 System Architecture and Design

 Modeling and Simulation

 Risk Management in SE

 Systems Integration and Interface Management

 Verification, Validation, and Testing

 Quality Assurance and Continuous Improvement

 Systems Engineering Management and Leadership

 PAC and agnostic PAC learning models

 Learning via uniform convergence

 Concentration-of-measure inequalities

 Bias-complexity tradeoff

 Vapnik-Chervonenkis dimension

 Nonuniform learning

 Model selection and validation

 Regularization

 Elementary algorithms (e.g., linear predictors, boosting, stochastic gradient descent, SVMs)

 Fundamentals of AI hardware architectures (GPUs, TPUs, FPGAs, and neuromorphic chips, memory architectures for AI workloads)

 Algorithm-hardware Co-design (optimization of AI algorithms considering hardware constraints, hardware design exploration)

 Energy efficiency and performance optimization (techniques for reducing power consumption, acceleration of matrix operations)

 Security and reliability (hardware-based security mechanisms for AI, fault tolerance and robustness)

 Software tools and frameworks (overview of available tools, practical application of selected tools)

 Application-specific optimization (case studies from various domains, design of AI hardware for specific application scenarios)

 Introduction

 Orbital Mechanics

 Satellite Launch Systems

 The Space Segment

 The Ground Segment

 Space System Project Management

 Space System Engineering

 The Communication Link

 Satellite Based Navigation

 Environment Perception

 Moving, Braking, Steering

 Communication

 Motion and Odometry

 Local Navigation

 Localization

 Sensor Fusion

 Motion Planning

 Testing and Simulation of Autonomous Vehicles

 Regulations and Standards

Depending on the topic, students are introduced to at least one current topic from research and/or practice in electronics engineering. Conceptual issues are discussed, methodological knowledge is imparted and what has been learned is applied to practicalwork. Examples of possible topics are

 Design of hardware for intelligent systems

 Artificial Intelligence for autonomous vehicles

 Design of automation systems

 Environmental research by remote sensing

 Greenhouse gas monitoring

 Introduction to EEP: Subjects are related to the Electronics Engineering program and

are usually inspired by current research projects in institutes i3m, IWSS and IAT

 Methods on scientific investigations in electronics engineering using literature and internet support

 Team work

 Project implementation, scheduling, monitoring and control

 Function, performance and application of project relevant engineering components, design tools and measurement equipment within a defined research project on optics, electronics, microsystems, communications, measurement and instrumentation

 Methods on evaluation of results, documentation and presentation techniques

 Introduction to EEP: Subjects are related to the Electronics Engineering program and

are usually inspired by current research projects in institutes i3m, IWSS and IAT

 Methods on scientific investigations in electronics engineering using literature and

internet support

 Team work

 Project implementation, scheduling, monitoring and control

 Function, performance and application of project relevant engineering components,

design tools and measurement equipment within a defined research project on

optics, electronics, microsystems, communications, measurement and instrumenta-

tion

 Methods on evaluation of results, documentation and presentation techniques

 Foundations of Group Behaviour

 Understanding Work Teams

 Communication

 Leadership

 Power and Politics

MODERN CONCEPTS OF PROJECT MANAGEMENT I & II:

 Methods of classical and agile project management

 Understanding working in teams

 Kanban and visual planning tools

TECHNOLOGY IN SOCIETY I

 History of technological inventions, paradigm shifts for societies, socio-technical

regimes and ideas of humanMScEE Module Manual Page 66

 Social science/ sociological concepts (norms, values, social structure, inequalities…)

 Selected historical case studies (e.g. automobile, jetliner)

 Problem-based learning cycle

TECHNOLOGY IN SOCIETY II

 Social science approaches for technology in society (e.g. STS, social constructivist,

ANT) and sociological concepts for analysis

 Selected empirical studies on laboratory work and engineering science and real-

world problems (e.g. digital inovations, artificial intelligence, automation…)

 Ethical criteria

 Problem-based learning cycle

RESEARCH METHODS I:

 Research and scientific work

 Research ethics and rules of good scientific practiceMScEE Module Manual Page 68

 Dealing with scientific literature,

citation

 Planning and writing scientific essays

 Scientific lecturing, presentation and communication

RESEARCH METHODS II:

 Finding a topic and beginning the scientific work

 Project and time management

 Documentation and reporting

 Scientific lecturing, scientific presentation and scientific communication

 Texts for the public, graphic design and poster design

 Project proposal and motivation letter

 Patents

 Entrepreneurship

Learning outcomes:

German courses refer to the Common European Framework of Reference (CEFR); learning outcomes are given here

for levels A 1 and A 2:

A 1= Can understand and use familiar everyday expressions and very basic phrases aimed at the satisfaction of needs of

a concrete type. Can introduce him/herself and others and can ask and answer questions about personal details

such as where he/she lives, people he/she knows and things he/she has. Can interact in a simple way provided the

other person talks slowly and clearly and is prepared to help.

A 2= Can understand sentences and frequently used expressions related to areas of most immediate relevance (e.g. very

basic personal and family information, shopping, local geography, employment). Can communicate in simple and

routine tasks requiring a simple and direct exchange of information on familiar and routine matters. Can describe

in simple terms aspects of his/her background, immediate environment and matters in areas of immediate need.

In the Academic Project Consulting, professors of the program accompany the industrial project work of the students with regular meetings in small groups on the design and continuous review of the project structure. This creates a forum for professional and organizational exchange, as well as a framework for the scientific support of the student’s work, which ensures the transfer of knowledge in both directions

For this placeholder module, students are to select a specific module from the “Non-technical Electives” catalogue.

 Structure of solids

 Mechanical, electrical, magnetic and optical properties of solids

 Fundamentals of heat transfer and Diffusion

 Transducers for different quantities

 Concepts of different microsensors: Inertial sensors, thermal sensors, pressure and flow sensors, magnetic sensors

 Design of integrated systems

 Principles of microfluidics

 Concepts of microfluidic system

 ANOVA, MANOVA, Hypothesis testing

 Uncertainty in measurement

 Design of experiments

 EMC/EMI in measurement applications

 Interfaces and bus systems

 Sensor signal conditioning

 Examples of electrical measurement of non-electrical properties

 Probability Theory: Random Variables, Distribution Functions, Expectation Operator, Vector-valued Random Variables, Transformations of Random Variables, Convergence Concepts, Laws of Large Numbers, Central Limit Theorems

 Stochastic Processes: Fundamentals, Some Particular Processes, Stationary Processes, Stochastic Limiting Operations, Spectral Analysis of Stationary Processes, Systems with Stochastic Inputs, Special Discrete Time Parameter Models

 Signal Detection: Neyman-Pearson Hypothesis Testing, Bayes Hypothesis Testing, Bayesian Approach, Maximum Likelihood Ratio Test, Non Parametric Tests

 Parameter Estimation: Sufficient Statistic, Linear Least Squares Estimation, Confidence Intervals, Maximum Likelihood Estimation, Bayesian Estimation

 Recursive estimation of stochastic processes: Kalman filtering

For this placeholder module, students are to select a specific module from the “Technical Electives Catalogue”. The program can be studied with a study profile in either “Development and Fabrication of Intelligent Systems” or “Application of Intelligent systems”, if they complete at least four technical elective modules assigned to one pro-file and write their Master’s thesis in a field matching the same profile. The respective study profile will be specified in the graduation certificate. For each Technical Elective it is marked in the module description which profile(es) (one or both) it is assigned to.

 Basic knowledge of cleanroom, vacuum and plasma technology

 Process steps of microfabrication including film deposition, lithography, etching, doping, wafer bonding and packaging

 Measurement techniques for process control and characterization of microsystems

 Introduction to fiber optic test and measurement

 Optical power measurement

 Polarization measurement

 Spectral Analysis

 Diffraction of Light and Measurement Applications

 Introduction

 Repetition of Wave Theory

 Microwave Network Analysis

 Impedance Matching and Tuning

 Microwave Passive Structures

 Noise in Two-Ports

 Microwave Amplifier Design

 Mixer and Oscillator

 Microwave Systems

 Image Processing

- Introduction to image processing

- System theoretic concepts of imaging systems

- Pixel and region processing

- Detection, segmentation, feature extraction and classification

 Pattern Recognition

- Introduction to pattern recognition

- Feature selection techniques

- Classifier concepts

- Deep Neural Networks

 Automatic target recognition systems

 Deep Generative Networks

 Explainable AI

 Typical laser applications: laser cleaning, rapid prototyping, medical applications, laser annealing

 Characterization of laser radiation

 Development of beam delivery and beam shaping systems

 Application of short pulse laser systems

 Generation of short pulses

 Laser micro processing

 Optical metrology and spectroscopy

 Fundamentals of Ocean Acoustics

 Sound Propagation Modeling

 Sonar Antenna Design

 Sonar Signal Processing

 Array Processing

 Bandpass/baseband representations

 Path loss and shadowing

 Multipath propagation

 Statistical channel modeling (WSSUS, Rayleigh, Rice)

 Receive diversity (e.g., maximal ratio combining, equal gain combining)

 Transmit diversity (e.g., Beamforming, Alamouti space time coding)

 Multicarrier modulation

 The OFDM air interface

 Direct-sequence spread spectrum

 Frequency-hopping spread spectrum

 Spreading sequences & rake receiver

 Design microelectronic circuits on printed-circuit board (PCB) and integrated-cir-

cuit (IC) level

 Amplifiers, integrators, filters, converters and auxiliary circuits

 Interfacing and aggregating microelectronic circuits

 Fundamental physics for optical metrology

 Detection of optical radiation

 Various types of interferometer

 Basics and applications of Shack-Hartmann wavefront sensors

 Introduction to Optical Coherence Tomography

 Ray Tracing in measurement

 Light Detection and Ranging

 Optical sensors

Depending on the topic, students are introduced to at least one current topic from research and/or practice in electronics engineering. Conceptual issues are discussed, methodological knowledge is imparted and what has been learned is applied to practical work. Examples of possible topics are

 Design of hardware for intelligent systems

 Artificial Intelligence for autonomous vehicles

 Design of automation systems

 Environmental research by remote sensing

 Greenhouse gas monitoring

 Introduction to EEP: Subjects are related to the Electronics Engineering program and

are usually inspired by current research projects in institutes i3m, IWSS and IAT

 Methods on scientific investigations in electronics engineering using literature and

internet support

 Team work

 Project implementation, scheduling, monitoring and control

 Function, performance and application of project relevant engineering components,

design tools and measurement equipment within a defined research project on

optics, electronics, microsystems, communications, measurement and instrumenta-

tion

 Methods on evaluation of results, documentation and presentation techniques

 Foundations of Group Behaviour

 Understanding Work Teams

 Communication

 Leadership

 Power and Politics

MODERN CONCEPTS OF PROJECT MANAGEMENT I & II:

 Methods of classical and agile project management

 Understanding working in teams

 Kanban and visual planning tools

TECHNOLOGY IN SOCIETY I

 History of technological inventions, paradigm shifts for societies, socio-technical

regimes and ideas of humanMScEE Module Manual Page 66

 Social science/ sociological concepts (norms, values, social structure, inequalities…)

 Selected historical case studies (e.g. automobile, jetliner)

 Problem-based learning cycle

TECHNOLOGY IN SOCIETY II

 Social science approaches for technology in society (e.g. STS, social constructivist,

ANT) and sociological concepts for analysis

 Selected empirical studies on laboratory work and engineering science and real-

world problems (e.g. digital inovations, artificial intelligence, automation…)

 Ethical criteria

 Problem-based learning cycle

RESEARCH METHODS I:

 Research and scientific work

 Research ethics and rules of good scientific practiceMScEE Module Manual Page 68

 Dealing with scientific literature,

citation

 Planning and writing scientific essays

 Scientific lecturing, presentation and communication

RESEARCH METHODS II:

 Finding a topic and beginning the scientific work

 Project and time management

 Documentation and reporting

 Scientific lecturing, scientific presentation and scientific communication

 Texts for the public, graphic design and poster design

 Project proposal and motivation letter

 Patents

 Entrepreneurship

Learning outcomes:

German courses refer to the Common European Framework of Reference (CEFR); learning outcomes are given here

for levels A 1 and A 2:

A 1= Can understand and use familiar everyday expressions and very basic phrases aimed at the satisfaction of needs of

a concrete type. Can introduce him/herself and others and can ask and answer questions about personal details

such as where he/she lives, people he/she knows and things he/she has. Can interact in a simple way provided the

other person talks slowly and clearly and is prepared to help.

A 2= Can understand sentences and frequently used expressions related to areas of most immediate relevance (e.g. very

basic personal and family information, shopping, local geography, employment). Can communicate in simple and

routine tasks requiring a simple and direct exchange of information on familiar and routine matters. Can describe

in simple terms aspects of his/her background, immediate environment and matters in areas of immediate need.

In the Academic Project Consulting, professors of the program accompany the industrial project work of the students with regular meetings in small groups on the design and continuous review of the project structure. This creates a forum for professional and organizational exchange, as well as a framework for the scientific support of the student’s work, which ensures the transfer of knowledge in both directions

For this placeholder module, students are to select a specific module from the “Non-technical Electives” catalogue.

 Introduction to the state of the art

 SystemVerilog Language Basics

 SystemVerilog Assertions

 SystemVerilog classes, parallel blocks, interprocess communication/thread control

 Constrained Randomization

 Functional Coverage

 Introduction into UVM

 Working with Questa tools

 Types and use of acquisition hardware

 Interfaces and bus systems

 Software tools for automated measurements and signal processing

 CADA project: DAQ with uC

 Information measures

 Source coding theorem

 Channel coding theorem

 Source-channel separation

 Differential entropy

 AWGN channel

 Finite fields

 Linear block codes

 Codes and polynomials

 Decoding methods and error bounds

 The students deal with a current scientific question and, for the most part,

indepen-dently develop the current state of research on this. In thesis work,

students have to show that they are able to treat a scientific or technical subject

self-directed within a given period of time and to integrate it into a larger

interdisciplinary context.

 The development / research task can be carried out in a university laboratory, in

industry or at a partner institution in Germany or abroad, as desired.

 The written part should be completed in English (exceptions in German language

have to be approved by the examination board).

 The results of the work are presented and discussed twice in the master’s seminar.

 In a final colloquium, the subject will be presented and discussed.

 The students deal with a current scientific question and, for the most part,

indepen-dently develop the current state of research on this. In thesis work,

students have to show that they are able to treat a scientific or technical subject

self-directed within a given period of time and to integrate it into a larger

interdisciplinary context.

 The development / research task can be carried out in a university laboratory, in

industry or at a partner institution in Germany or abroad, as desired.

 The written part should be completed in English (exceptions in German language

have to be approved by the examination board).

 The results of the work are presented and discussed twice in the master’s seminar.

 In a final colloquium, the subject will be presented and discussed.