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 (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.

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)
  • 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”.

Lab Courses/Practicals (choose 7.5 ECTS):

  • Audio Processing Laboratory (2.5 ECTS, WS/SS, 894349)
  • Digital Communications (2.5 ECTS, WS/SS, 93511)
  • Digital Signal Processing (2.5 ECTS, WS, 97520)
  • Image and Video Signal Processing on Embedded Systems (2.5 ECTS, WS, 97525)
  • Machine Learning and Systems (2.5 ECTS, WS, 47574)
  • 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)

Seminar (choose 2.5 ECTS):

  • Audio Processing Seminar (2.5 ECTS, WS/SS, 330542)
  • Selected Topics in Communications (2.5 ECTS, WS, 775681)
  • Selected Topics in Machine Learning (2.5 ECTS, WS/SS, 92374)
  • Selected Topics in Multimedia Communications and Signal Processing (2.5 ECTS,WS/SS, 914949)

Technical Electives (choose 15 ECTS):

  • Advanced C++ Programming (2.5 ECTS, WS/SS, online course via VHB, 44466)
  • 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 (2.5 ECTS, WS, 92355)
  • Computer Graphics (5 ECTS, WS, 43822)
  • Convex Optimization in Communications and Signal Processing (5 ECTS, WS, 96850)
  • Deep Learning (5 ECTS, WS, 901895)
  • Diagnostic Medical Image Processing (5 ECTS, WS/SS, online course via VHB, 44150)
  • Generative Models for Signal Processing (2.5 ECTS, WS, 44973)
  • 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, 451971)
  • Advanced Topics in Deep Learning (5 ECTS, SS, 42800)
  • Audio Processing for the Internet of Things (2.5 ECTS, SS, 44522)
  • Cognitive Neuroscience for AI Developers (5 ECTS, SS, 44445)
  • 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)
  • Perception in Robotics (5 ECTS, SS, 42801)
  • Radar, RFID and Wireless Sensor Systems (RWS) (5 ECTS, SS, 96316)
  • Reinforcement Learning (5 ECTS, SS, 93185)
  • Selected Topics in ASC (5 ECTS, SS, 48451)
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”.

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. Make sure to first contact your potential supervising professor before engaging in any discussions with a possible industry partner.

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. Please note: 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.

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 who do not have German language proficiency on level B2 or higher must earn all 15 ECTS with German language courses.
The elective modules from non-engineering subjects are graded and will be included in the calculation of the final grade in CME.

If you are a native speaker of German or if you already have verifiable German language proficiency on level B2, please contact the CME degree program coordinator. In that case, you will receive a confirmation that you are exempt from the obligation to take German language courses.

If a student reaches level B2 German language proficiency and still has some ECTS of non-engineering electives open, he or she is allowed to earn the remaining ECTS with other non-engineering electives.

Examples:

Case 1: A student starts with no knowledge of German. He or she is obliged to earn 15 ECTS with German language courses: A1.1 Deutsch (5 ECTS) + A1.2 Deutsch (5 ECTS) + A2.1 Deutsch (5 ECTS). All three German language courses are graded and influence the final grade in CME. It is not possible to exchange any of the German language courses with another non-engineering elective.

Case 2: A student starts with advanced knowledge of German. He or she takes B2.1 Deutsch (5 ECTS) + B2.2 Deutsch (5 ECTS). When succesfully finishing the course B2.2 Deutsch, the student reaches German language proficiency level B2. He or she can choose how to earn the remaining 5 ECTS with non-engineering electives. The student could, for example, take another German course or another non-engineering elective such as “Academic English”. The grades from the German courses B2.1 Deutsch and B2.2 Deutsch will be credited and influence the final grade in CME. It is not possible to exchange these grades with another non-engineering elective.

Case 3: A student holds a Goethe-Zertifikat B2 when starting their studies in CME. He or she is not obliged to take German language courses, but can choose from the catalogue of non-engineering electives.

It is not allowed to exchange an obligatory German language course with another non-engineering subject.

Master’s thesis (30 ECTS)

A Master’s thesis is a piece of original scientific work conducted under the direction of a faculty advisor. The Master’s thesis is intended to demonstrate students’ ability to solve scientific problems in the field of communication and multimedia engineering independently.

Topics are announced on the chairs’ websites or can be requested directly from the professors. You may also suggest a topic yourself. All full-time university lecturers teaching at the Department of Electrical Engineering (EEI ) are entitled to supervise Master’s theses. The requirements of the Master’s thesis are to be set in such a way that it can be completed within six months with a processing time of approximately 900 hours.

Prerequisite for admission to the Master’s thesis is that you have passed all compulsory modules and have acquired at least 80 ECTS points.

The thesis consists of a written part and an oral part. There is no mandatory length for the written part of a thesis. Most Master’s theses have between 50 and 80 pages. However, depending on the topic, more or fewer pages may be appropriate. If the written part is graded at least sufficient, you must present the results of your work in an oral presentation of approximately 30 minutes length with subsequent discussion. The date for the final presentation is set by the supervising university lecturer.

Make sure to adhere to the standards of good scientific practice. Meticulously reference all your sources and cite correctly. Plagiarism is a serious academic misconduct. If you need support, use the workshops and services of the FAU Writing Centre.