Course Contents
The course covers the following topics:
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[*]The basic concepts of stochastic
[*]The sampling theorem
[*]Discrete-time noise processes and their properties
[*]Description of noise processes in the frequency domain
[*]Linear time-invariant systems: FIR and IIR filters
[*]Filtering of noise processes: AR, MA, and ARMA models
[*]The Matched filter
[*]The Wiener filter
[*]Properties of estimators
[*]The method of least squares
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Literature
Lecture notes and slides can be downloaded here:
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[*][url]http://www.spg.tu-darmstadt.de[/url]
[*]Moodle platform
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Further reading:
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[*]A. Papoulis: Probability, Random Variables and Stochastic Processes. McGraw-Hill, Inc., third edition, 1991.
[*]P. Z. Peebles, Jr.: Probability, Random Variables and Random Signal Principles. McGraw-Hill, Inc., fourth edition, 2001.
[*]E. Hänsler: Statistische Signale; Grundlagen und Anwendungen. Springer Verlag, 3. Auflage, 2001.
[*]J. F. Böhme: Stochastische Signale. Teubner Studienbücher, 1998.
[*]A. Oppenheim, W. Schafer: Discrete-time Signal Processing. Prentice Hall Upper Saddle River,1999.
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- Lehrende: Christian Eckrich
- Lehrende: Marius Pesavento
- Lehrende: Abdelhak Zoubir