Cardinal Stefan Wyszynski University in Warsaw - Central Authentication System
Strona główna

Digital signal processing WM-I-CPS
Lectures (WYK) Winter semester 2021/22

Information on classes (common for all the groups)

Class hours: 30
Places limit: (no limit)
Bibliography:

Obligatory:

Oppenheim A.V., Schafer W. - Cyfrowe przetwarzanie sygnałów, WKiŁ, Warszawa 1979

Lyons R. G. - Wprowadzenie do cyfrowego przetwarzania sygnałów, WKiŁ, Warszawa 1999

Cytowski J., Kępski R., Cyfrowe przetwarzanie sygnałów elektrokardioigraficznych, Wydawnictwo Naukowe UKSW, Warszawa, 2017

Complementary:

Oppenheim A.V. - Sygnały cyfrowe, przetwarzanie i zastosowania, WNT, Warszawa 1982

J. Cytowski, J. Gielecki, A. Gola, Przetwarzanie obrazów medycznych. Teoria. Algorytmy. Zastosowania. Oficyna wydawnicza EXIT, Warszawa 2009

Learning outcomes:

Can perform the parameterization of the ECG I1_U01 signal

Can use speech recognition algorithms and perform speech coding with the use of linear signal prediction I1_U02

Can implement convolution and correlation algorithms using the Fast Fourier Transform (FFT), perform the estimation of the signal frequency using the window function and create the I1_U03 spectrogram

Can design selected analog and digital filters I1_U05

Is able to create technical documentation of the project of the analysis of sound signals I1_U15

Can perform basic signal analysis operations such as sampling, frequency analysis using DFT, generating the histogram I1_U18

Is aware of the fragmentation of his own knowledge in the field of digital signal processing and is ready to individually expand his skills I1_K01

Is ready to team work on IT projects with signal processing I1_K03

Assessment methods and assessment criteria:

Practical programming project

Theoretical exam

List of topics:

Digital signal analysis

Analog signal sampling. Generating of discrete signals. Histogram.

Introduction to frequency analysis using DFT, sampling illustration.

Fast Fourier Transform algorithms.

Frequency estimation: the window function.

Spectrogram.

Zeros and poles of transfer function.

Analog filters of Butterworth, Chebyshev and elliptical.

IIR digital filters. Recursive digital signal filtering.

FIR digital filters. Non-recursive digital signal filtering by convolution.

Adaptative filters and applications.

Fast convolution and correlation algorithms using FFT.

Speech coding using linear prediction.

ECG parametrisation algorithms.

Classification algorithms - speech recognition.

Computer vision.

Teaching methods:

lectures 30 hours

laboratories 30 hours

Class groups

see this on class schedule

Group Timeframe(s) Lecturers Places Number of students in group / places limit Actions
1 every Thursday, 9:45 - 11:15, room e-learning
Jerzy Cytowski 12/17 details
All lectures are taking place in this building:
(in Polish) e-learning
Course descriptions are protected by copyright.
Copyright by Cardinal Stefan Wyszynski University in Warsaw.
ul. Dewajtis 5,
01-815 Warszawa
tel: +48 22 561 88 00 https://uksw.edu.pl
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