Digital signal processing

Laboratory: SPLab
Garant: prof. Ing. Zdeněk Smékal, CSc.
Area of study: Data-mining, Human-machine interaction, Non-orthogonal signal representation, Acoustic signal processing, Biomedical signal processing
Level and semester: Master's studies, 2nd semester

Goal

The aim of the course is to present modern methods of digital signal processing that are based primarily on parametric and non-parametric spectral analysis, linear prediction and digital signal processing banks of multirate digital filters.

Learning outcomes and competences

The student will be equipped for establishing spectral properties of deterministic and random signals using various base functions (Fourier analysis, wavelets) for multiple resolution. He will know how to use multirate filter banks (applied, for example, in methods of audio- and video-signal compression, ADSL transmission, etc.).

Annotation

Characteristics and classification of discrete signals and systems. Operations with signals and examples of systems. Spectral analysis using FFT. Spectrograms and moving spectra. Discrete Hilbert transform. Representation of pass-band signals.Power spectral density and its estimation. Non-parametric methods. Linear prediction analysis. Autoregression processes, moving average. Parametric methods for calculating power spectral density. Adaptive filtering. Type LMS and RLS gradient algorithms. Adaptive block filters. Decimation and interpolation. Transversal and polyphase filters. Banks of filters with perfect reconstrruction. Half-band filters. Wavelet transformation. Signal analysis with multiple resolution. Compression of audio-signals in telecommunications.

University link:

http://www.vutbr.cz/en/studies/ects-catalogue/course-detail?apid=112644

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