The students know the basics for digital signals and digital systems and how they can be described mathematically in the time and frequency domain. They understand the concepts in digital communication.
Additionally, the students can design causal systems and knows the importance and the power of the DFT/FFT and z-transformation.
Further they are able to design multi-rate systems and special filter topologies.

Knowledge about analog signals and systems.

The course deals with digital signals and systems.
• Introduction of fundamental digital signals and digital systems (e.g. FIR-, IIR- Filter). Theoretical discussion of main properties (e.g.. stability, causality) and different options of representation in time and frequency domain. Study of many practical exercises using Matlab/Simulink environment
• Design of causal systems (FIR-,IIR-Filter)
• Discrete Fourier Transform (DFT) and its fast realizations (FFT). Practical applications (e.g. evaluation in labs using FFT, system identification based on FFT, ...)
• Sampling rate conversion, multi-rate systems and filter banks
• Special filter topologies (e.g. Cascaded-Integrator-Comb -Filter (CIC), lattice wave digital filter (LWDF), ...)
• Adv. digital communication concepts as well as the implementation of digital algorithms will be evaluated by means of digital signal

H.W. Schüßler. Digitale Signalverarbeitung, Springer, Berlin, 2008.
A.V. Oppenheim and R. W. Schafer with J.R. Buck. Discrete Time Signal Processing. Prentice Hall, Upper Saddle River, 2014.
K.D. Kammeyer and K. Kroschel. Digitale Signalverarbeitung: Filterung und Spektralanalyse. Teubner, Stuttgart, 2018.
T.W. Parks and C.S. Burrus. Digital Filter Design. J. Wiley & Sons, New York, NY, USA, 1987.

Integrated course - teaching & discussion, demonstration, exercises and practical examples in the lab, home work

Written examination and collaboration