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227-0101-00L 4 Credits
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Stochastic models and signal processing

Stochastische Modelle und Signalverarbeitung

Lecturers & Examiners: Prof. Dr. Hans-Andrea Loeliger
VVZ CR 3.4

Last Updated: 2026-02-05 14:53:09

Objective

The course introduces some fundamental topics of digital signal processing with a bias towards applications in telecommunications. The two main themes are "linearity" and "probability". In addition to linear filtering, its "inversion" (equalization) is also encountered repeatedly.

Content

Discrete-time linear systems and the z-transform; discrete time and continuous time: forth and back; digital filters; elements of probability theory; discrete-time stochastic processes; elements of detection and estimation theory; Viterbi algorithm; linear estimation and filtering; Wiener filter; LMS algorithm.

Resources

Lecture Notes

Lecture Notes.

General Information

Language
German
Frequency
Yearly recurring

Examination

Type
session examination
Mode
oral 30 minutes

Course Components

Type Title Time & Place Hours
lecture with exercise Stochastische Modelle und Signalverarbeitung
  • Tue 13:15-17:00 (ETF C 1)
4 h weekly

Offered In