Subjects

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Digital Signal and Image Processing - D445019

Title:	Číslicové zpracování signálů a obrazů
Guaranteed by:	Department of Computing and Control Engineering (445)
Faculty:	Faculty of Chemical Engineering
Actual:	from 2019 to 2020
Semester:	winter
Points:	winter s.:0
E-Credits:	winter s.:0
Examination process:	winter s.:
Hours per week, examination:	winter s.:0/0, other [HT]
Capacity:	unknown / unknown (unknown)
Min. number of students:	unlimited
Language:	Czech
Teaching methods:	full-time
Teaching methods:	full-time
Level:
For type:
Additional information:	http://uprt.vscht.cz/prochazka/pedag/lectures/SP0_MATLAB_2006EN.pdf
Note:	course is intended for doctoral students only can be fulfilled in the future

Guarantor:	Procházka Aleš prof. Ing. CSc.

Examination dates Schedule

Annotation -

Last update: Procházka Aleš prof. Ing. CSc. (20.01.2018)

The subject presents fundamental mathematical, algorithmic and programming tools for digital signal and image analysis, including z-transform, discrete Fourier and wavelet transforms and solution of difference equations. A special attention is paid to the description of discrete systems in time and frequency domains, to methods of spectral analysis, to adaptive methods of signal processing and to digital filters of multichannel and multidimensional signals. Applications and case studies include tools and methods of data acquisitions and their processing in selected engineering and biomedical problems.

Aim of the course -

Last update: Procházka Aleš prof. Ing. CSc. (20.01.2018)

Students will know how

(i) to analyze time series and images by discrete Fourier and wavelet transforms,

(ii) to use z-transform for discrete systems description,

(iii) to apply digital filters in time and frequency domains,

(iv) to use digital signal processing methods for real data analysis

(v) to propose computational environment for analysis of real (biomedical) data

Descriptors -

Last update: Procházka Aleš prof. Ing. CSc. (05.01.2018)

Signal and system description, z-transform, multidimensional signal analysis, discrete Fourier transform, digital filters, wavelet transform, image analysis and processing, visualization, 3D modelling

Literature -

Last update: Procházka Aleš prof. Ing. CSc. (05.01.2018)

Z: J. Uhlíř, P. Sovka, Číslicové zpracování signálů, Vydavatelství ČVUT, 2002

Z: http://uprt.vscht.cz/prochazka/pedag/ lectures/ATHENS_DSP.pdf

D: T. Bose: Digital Signal and Image Processing, Wiley, 2004

D: J. Jan, Číslicová filtrace, analýza a restaurace signálů, BEN 2004

D: Vaseghi S.V.: Multimedia Signal Processing, Wiley, 2007

D: WIKIBOOK: Signals and Systems, https://en.wikibooks.org/wiki/Signals_and_Systems, 2018

Learning resources -

Last update: Procházka Aleš prof. Ing. CSc. (05.01.2018)

http://uprt.vscht.cz/prochazka/pedag/lectures/ATHENS_DSP.pdf

http://uprt.vscht.cz/prochazka/pedag/lectures/SP0_MATLAB_2006EN.pdf

Teaching methods -

Last update: Procházka Aleš prof. Ing. CSc. (05.01.2018)

Lectures and practical verification of proposed algorithms in the computer laboratory.

Requirements to the exam -

Last update: Procházka Aleš prof. Ing. CSc. (20.01.2018)

During studies of this subject it is necessary either to submit the own paper using signal and image processing methods in the area of own research or to evaluate three projects devoted to specific signal and image processing problems and their solution in MATLAB.

Syllabus -

Last update: Procházka Aleš prof. Ing. CSc. (05.01.2018)

1. Fundamentals of computational, programming and visualization system MATLAB / SIMULINK

2. Computational intelligence in signal processing

3. Description of signals and systems, Z-transform

4. Solution of difference equations, discrete and frequency transfer functions, stability

5. Spectral analysis, discrete Fourier transform, windowing

6. The short time Fourier transform, analysis of multidimensional signals

7. Discrete Wavelet transform

8. Digital filters in time and frequency domains

9. Description of filters, construction

10. Rejection of noise signal components

11. Adaptive methods of signal processing, computational intelligence

12. CASE STUDY 1: Spectral analysis in signal analysis

13. CASE STUDY 2: Digital filters

14. CASE STUDY 3: Image analysis

Entry requirements -

Last update: Procházka Aleš prof. Ing. CSc. (05.01.2018)

Fundamentals of computer intelligence, fundamentals of numerical methods

Registration requirements -

Last update: Procházka Aleš prof. Ing. CSc. (20.01.2018)

Mathematics 1, 2

Course completion requirements -

Last update: Procházka Aleš prof. Ing. CSc. (20.01.2018)

Participation on the final colloquium with the presentation and discussion of a selected research topic.