
Digital Signal Processing
Content
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.
Prerequisites
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
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
DSP Demo Program
The DSP Demo, produced by Le Duan, currently runs on Mac OS X.
It is open source at https://github.com/QtSignalProcessing/QtSignalProcessing.