Digital Signal Processing


This one-semester graduate course provides a first introduction to the classical theory of digital signal processing including the following topics:

  • Mathematical foundations: Complex calculus
  • Linear time-invariant systems
  • Sampling, reconstruction, quantization
  • Convolution, correlation
  • Digital Filters
  • Fourier Transformation

complemented by lab sessions, both pen and paper as well as practical Matlab exercises. There will be one extended Matlab assignment dealing with the processing of audio signals.

Lecture in ZEuS Tutor in ZEuS


None, if taken as a master course. If taken as an advanced course in the bachelor program:

  • basic math courses offered in our bachelor programs
  • algorithms and data structures
  • introduction to computer science including programming

Course works and credits

The course ends with a final exam (either oral or written, depending on the number of course participants). 50% of the marks for homework assignments is required for the admission to this final exam. If you earn at least 70% of the marks for homework assignments, the final grade is 1/3 of a grade better than the exam grade. If you earn at least 90 %, the bonus is 2/3 of a grade.

Lab Sheets

Lab sheet 12

Due: 03.02.2018

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Lab Sheet 11

Due: 27.01.2018

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Lab Sheet 10

Due: 20.01.2018

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Lab Sheet 9

Due: 13.01.2018

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Lab Sheet 7

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Lab Sheet 6

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Lab Sheet 5

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Lab Sheet 4

Due: 25.11.2017

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Lab Sheet 3

Due: 18.11.2017

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Lab Sheet 2

Due: 11.11.2017

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Lab Sheet 1

Due: 04.11.2017

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Please submit your solutions as Latex-generated PDFs by e-mail and attach Matlab code if required. Please name your submission in the following way: labsheet_number_firstname_lastname. e.g., for the lab sheet 1, my submission name is labsheet_01_hanhe_lin.

  • Alan Oppenheim, Ronald Schafer, John Buck, Discrete-time Signal Processing, Prentice-Hall, 2010.
  • Alan Oppenheim, Ronald Schafer, John Buck, Zeitdiskrete Signalverarbeitung, 2. Auflage, Pearson Studium, 2004.
  • Vinay Ingke, John Proakis, Digital Signal Processing using MATLAB, Third Edition, Cengage Learning, 2012.

Literature on Complex Calculus

DSP Book References

Digital Signal Processing Using MATLAB

This supplement to any standard DSP text is one of the first books to successfully integrate the use of MATLAB in the study of DSP concepts. In this book, MATLAB is used as a computing tool to explore traditional DSP topics, and solve problems to gain insight. This greatly expands the range and complexity of problems that students can effectively study in the course. Since DSP applications are primarily algorithms implemented on a DSP processor or software, a fair amount of programming is required. Using interactive software such as MATLAB makes it possible to place more emphasis on learning new and difficult concepts than on programming algorithms. Interesting practical examples are discussed and useful problems are explored. This updated second edition includes new homework problems and revises the scripts in the book, available functions, and m-files to MATLAB V7.

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DSP First: A Multimedia Approach

This hands on, multi-media package provides a motivating introduction to fundamental concepts, specifically discrete-time systems, for beginning engineering readers. Designed and written by experienced and well- respected authors, this class-tested learning package can also be used as a self-teaching tool for anyone eager to discover more about DSP applications, multi-media signals, and MATLAB. Unique features, such as visual learning demonstrations, MATLAB laboratories and a bank of solved home-work problems are just a few things that make this an essential learning tool for mastering fundamental concepts in today's electrical and computer engineering institutions.

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Signal Processing First

This text is derived from DSP First: A Multimedia Approach, published in 1997, which filled an emerging need for a new entry-level course not centered on analog circuits in the ECE curriculum. It was also successfully used in 80 universities as a core text for linear systems and beginning signal processing courses. This derivative product, Signal Processing First [SPF] contains similar content and presentation style, but focuses on analog signal processing.

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The Scientist and Engineer's Guide to Digital Signal Processing

Clear and concise explanations of practical DSP techniques. Written for scientists and engineers needing the power of DSP, but not the abstract theory and detailed mathematics.

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Zeitdiskrete Signalverarbeitung

This is the standard text for introductory advanced undergraduate and first-year graduate level courses in signal processing. The text gives a coherent and exhaustive treatment of discrete-time linear systems, sampling, filtering and filter design, reconstruction, the discrete-time Fourier and z-transforms, Fourier analysis of signals, the fast Fourier transform, and spectral estimation. The author develops the basic theory independently for each of the transform domains and provides illustrative examples throughout to aid the reader. Discussions of applications in the areas of speech processing, consumer electronics, acoustics, radar, geophysical signal processing, and remote sensing help to place the theory in context. The text assumes a background in advanced calculus, including an introduction to complex variables and a basic familiarity with signals and linear systems theory. If you have this background, the book forms an up-to-date and self-contained introduction to discrete-time signal processing that is appropriate for students and researchers.

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Dirac Comb

A good reference regarding Dirac Comb, written by William Wicock, University of Washington. 

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DSP Demo Program

The DSP Demo, produced by Le Duan, currently runs on Mac OS X.

It is open source at


DSP Video Lectures

Interactive Online Applets