Module Catalogue

Module Book

The module books have been retrieved from campo on the date indicated. The information may be subject to change. For current information on courses see campo.

List of Modules

The Master’s degree program CME is designed as a two-year full-time postgraduate program (4 semesters). In order to graduate students need to earn a total of 120 ECTS (including 30 ECTS for the Master’s thesis).

Compulsory Modules

Compulsory Modules (30 ECTS):

  • Digital Communications (5 ECTS, WS, 47800)
  • Digital Signal Processing (5 ECTS, WS, 93500)
  • Information Theory and Coding (5 ECTS, WS, 93601)
  • Statistical Signal Processing (5 ECTS, WS, 96430)
  • Mobile Communications (5 ECTS, SS, 43141)
  • Image and Video Compression (5 ECTS, SS, 96310)
Compulsory Modules can be replaced by Compulsory Elective Modules (Technical Courses) if equivalent courses have been completed in earlier studies.
Students who started studying before winter semester 2023/24 (PO-Version 2011) need to complete 35 ECTS of Compulsory Modules. In addition to the modules above they need to complete Speech and Audio Signal Processing.

Compulsory Elective Modules, Technical Courses

Technical Courses (choose 10 ECTS):

  • Advanced Optical Communication Systems (5 ECTS, WS, 621649)
  • Advanced Topics in Perceptual Audio Coding (2.5 ECTS, WS, 96875)
  • Equalization and Adaptive Systems for Digital Communications (2.5 ECTS, WS, 43400)
  • Image, Video, and Multidimensional Signal Processing  (5 ECTS, WS, 96312)
  • Machine Learning in Signal Processing (5 ECTS, WS, 48440)
  • Multiuser Information and Communications Theory (5 ECTS, WS, 687141)
  • Music Processing – Synthesis (2.5 ECTS, WS, 502007)
  • Music Processing – Analysis (2.5 or 5 ECTS, WS, 302148 or 639119)
  • Optical Communication Networks (2.5 ECTS, WS, 43000)
  • Pattern Recognition (5 ECTS, WS, 44130)
  • Signal Analysis (2.5 ECTS, WS, 250058)
  • Speech Enhancement (2.5 ECTS, WS, 788996)
  • Advanced Communication Networks (5 ECTS, SS, 151664)
  • Architectures for Digital Signal Processing (5 ECTS, SS, 96010)
  • Auditory Models (2.5 ECTS, SS, 947709)
  • Linear and Non-linear Fibre Optics (5 ECTS, SS, 267499)
  • MIMO Communication Systems (5 ECTS, SS, 96300)
  • Pattern Analysis (5 ECTS, SS, 44120)
  • Transmission and Detection for Advanced Mobile Communications (2.5 ECTS, SS, 43420)
  • Transforms in Signal Processing (2.5 ECTS, SS, 498723)
Students who started studying before winter semester 2023/24 (PO-Version 2011) only need to choose 5 ECTS of Technical Courses.
In campo Technical Courses are listed under “1730 Technische Wahlpflichtmodule/Technical courses”.

Compulsory Elective Modules, Lab Courses (Practicals)

Lab Courses/Practicals (choose 7.5 ECTS):

  • Audio Processing Laboratory (2.5 ECTS, WS/SS, 894349)
  • Digital Communications (2.5 ECTS, WS/SS, 293179)
  • Digital Signal Processing (2.5 ECTS, WS, 97520)
  • Image and Video Signal Processing on Embedded Systems (2.5 ECTS, WS, 97525)
  • Communications Systems Design (2.5 ECTS, SS, 92356)
  • Image and Video Compression (2.5 ECTS, SS, 97651)
  • Machine Learning in Signal Processing (2.5 ECTS, SS, 878210)
  • Mobile Communications (2.5 ECTS, SS, 97640)

Compulsory Elective Modules, Advanced Seminar

Seminar (choose 2.5 ECTS):

  • Audio Processing Seminar (2.5 ECTS, WS/SS, 330542)
  • Selected Topics in Multimedia Communications and Signal Processing (2.5 ECTS,WS/SS, 914949)
  • Selected Topics in Communications (2.5 ECTS, WS, 775681)

Compulsory Elective Modules, Research Internship

Research Internship (10 ECTS)

The research internship (Forschungspraktikum) should ideally be completed in the third semester after having passed all compulsory modules. The aim of the research internship is to provide some hands-on experience in research. It is usually conducted at a university chair.

Every chair of the Department Electrical Engineering (EEI) and the chair of Pattern Recognition are eligible to supervise the research internship. It is, however, recommended to choose a chair that is closely associated with the CME study program, e.g. LMS, IDC, AudioLabs or LIKE.

The research internship can also be conducted at a research-oriented company. In these cases it is nonetheless obligatory to find a supervising chair at either the Department Electrical Engineering (EEI) or the chair of Pattern Recognition.

The research internship has a workload of 10 ECTS (300 hours). For completion, a presentation of about 20 minutes has to be given and a report of 10 to 15 pages has to be written.

Before starting the research internship a task description needs to be filled in by the supervising chair. The task description lists the research goal, the start date and other details that help to clarify the extent, expectations and aim of the individual research internship. Please note that there is no specific form for the task description. Supervising chairs should use and, if needed, adapt the templates that they usually use in similar cases.

A registration in campo is not necessary to start the research internship. The supervisor informs the Examination Office as soon as the research internship has been completed. In campo the research internship is listed with the title from the task description. The research internship is not graded. It is a pass/fail achievement.

In case of questions on the technical details of the research internship, contact CME Study Advisor Dr.-Ing. Heinrich Löllmann.

Compulsory Elective Modules from Non-Engineering Subjects, Languages/Soft Skills

Languages/Soft Skills (15 ECTS)

The qualification goal of the elective modules from non-engineering subjects is to enable students to expand their technical competence profile through general language, social, methodological and personal competencies.

Students with no or few knowledge of German must take all 15 ECTS in German language courses.

Elective Modules, Technical Electives

Technical Electives (choose 15 ECTS):

  • Advanced C++ Programming (2.5 ECTS, WS/SS, online course via VHB, 44466)
  • Cognitive Neuroscience for AI Developers (5 ECTS, WS/SS, 44445)
  • Interventional Medical Image Processing (5 ECTS, WS/SS, online course via VHB, 44140)
  • Body Area Communications (2.5 ECTS, WS, 816185)
  • Advanced Networking LEx (5 ECTS, WS, 869547)
  • Communications Systems Design (5 ECTS, WS, 92355)
  • Computer Graphics (5 ECTS, WS, 43821)
  • Convex Optimization in Communications and Signal Processing (5 ECTS, WS, 96850)
  • Deep Learning (5 ECTS, WS, 901895)
  • Diagnostic Medical Image Processing (5 ECTS, WS, online course via VHB, 44150)
  • Introduction to Deep Learning (5 ECST, WS, 43405)
  • Machine Learning for Time Series (5 ECTS, WS, 428256)
  • Machine Learning in Communications (5 ECTS, WS, 668129)
  • Mathematical Optimization in Communications and Signal Processing (5 ECTS, WS, 48400)
  • Molecular Communications (5 ECTS, WS, 454183)
  • Radar Signal Processing (5 ECTS, WS, 44400)
  • Random Matrices in Communications and Signal Processing (5 ECTS, WS, 257359)
  • Virtual Vision (2.5 ECTS, WS, 96314)
  • Advanced Topics in Deep Learning (5 ECTS, SS, 42800)
  • Audio Processing for the Internet of Things (2.5 ECTS, SS, 44522)
  • Game Theory with Application to Information Engineering (5 ECTS, SS, 48432)
  • Channel Coding (5 ECTS, SS, 96270)
  • Channel Coding on Graphs (5 ECTS, SS, 412023)
  • Circuits and Systems of Transmission Techniques (5 ECTS, SS, 96410)
  • Computer Vision (5 ECTS, SS, 713618)
  • Human Computer Interaction (5 ECTS, SS, 645618)
  • Next Generation Mobile Communication Systems: 5G-Advanced and 6G (2.5 ECTS, SS, 96065)
  • Radar, RFID and Wireless Sensor Systems (RWS) (5 ECTS, SS, 96316)
  • Reinforcement Learning (5 ECTS, SS, 93185)
  • Selected Topics in ASC (5 ECTS, SS, currently not offered)
  • Self-organized Networks (5 ECTS, SS, 43960)
All courses listed in the section “Compulsory Elective Modules, Technical Courses” can also be taken as Technical Electives.
In campo Technical Electives are listed under “1800 Technische Wahlmodule/Technical Electives”.

Master's thesis

Master’s thesis (30 ECTS)

The Master’s thesis is intended to demonstrate students’ ability to solve scientific problems in the field of communication and multimedia engineering independently. All full-time university lecturers teaching at the Department of Electrical Engineering are entitled to supervise Master’s theses.