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227-0427-00L 4 Credits
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Signal and Information Processing: Modeling, Filtering, Learning

Lecturers & Examiners: Prof. Dr. Hans-Andrea Loeliger
VVZ CR n/a

Last Updated: 2026-02-05 14:55:15

Content

The course is an introduction to some basic topics in linear, nonlinear, and adaptive signal processing, with application examples from acoustics, communications, and biomedical signal processing. Topics: linear filters and filter banks, FFT and fast convolution, basics of wavelets, Hilbert spaces; adaptive filters, LMS and RLS, neural networks, support vector machines; hidden Markov models, Kalman filtering and smoothing, particle filters, factor graphs; application examples from acoustics, communications, and biomedical signal processing.

General Information

Language
English
Frequency
Yearly recurring

Examination

Type
session examination
Mode
oral 30 minutes

Course Components

Type Title Time & Place Hours
lecture with exercise Signal and Information Processing: Modeling, Filtering, Learning
  • Fri 08:15-12:00 (ETZ E 7)
4 h weekly

Offered In