Special Topics in Signal Processing (Guest Lectures)

List of previous lectures

Multirate Digital Signal Processing, SS 2018

Prof. Dr. Dietmar Wenzel, Rhode & Schwarz GmbH, TU Munich

Sampling rate conversion is a key factor, especially when it comes to the coupling of digital systems or to the compression of data. In this lecture, students learned the underlying theory and background, to design sampling rate converters, to employ various implementation forms, and to understand the economical aspects of different architectures. Examples for implementations of multirate signal processing architectures were given for audio, video and mobile communications.

Adaptive and Array Signal Processing, WS 2016/17

Prof. Dr. Rodrigo de Lamare, Pontifical Catholic University of Rio de Janeiro

Prof. de Lamare gave an overview of array signal processing for communications and radar with a focus on beamforming and direction of arrival estimation.

Contents: Fundamentals of Array Processing, Array Configurations, Discrete Time Models, Optimum and Robust MVDR Beamforming, Adaptive Beamforming, Direction of Arrival Estimation.

Channel Coding, SS 2016

Prof. Dr. Johannes Huber, University of Erlangen-Nuremberg

This lecture covered the fundamentals and applications of channel coding in digital communications, and provided insight into current research activities in this field.

Contents: Fundamentals of Block Coding, Linear Block Codes, Linear Cyclic Codes, BCH und RS Codes, Convolutional Codes, Turbo Codes, Principles and Limits for Information Combining, LDPC-Codes, Polar Codes, Coded Modulation.

Information Theory, SS 2015

Prof. Dr. Johannes Huber, University of Erlangen-Nuremberg

In this lecture, Prof. Huber gave an introduction to the basic terms and concepts of information theory, that are information, entropy, mutual information, information transmission, data compression, coding, and related topics.

Contents: Fundamentals of Information Theory, Source Coding, Characterization of Transmission Channels, Channel Capacity, Information Theory for Continuously Distributed Random Variables, Signal Distortions.