SubjectsSubjects(version: 955)
Course, academic year 2019/2020
  
Digital Signal and Image Processing - P445008
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: both
Points: 0
E-Credits: 0
Examination process:
Hours per week, examination: 3/0, other [HT]
Capacity: winter:unknown / unknown (unknown)
summer:unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Level:  
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
you can enroll for the course in winter and in summer semester
Guarantor: Procházka Aleš prof. Ing. CSc.
Vyšata Oldřich MUDr. Ph.D.
Is interchangeable with: AP445008
Examination dates   Schedule   
Annotation -
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.
Last update: Pátková Vlasta (29.05.2018)
Aim of the course -

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

Last update: Pátková Vlasta (29.05.2018)
Descriptors -

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

Last update: Pátková Vlasta (29.05.2018)
Literature -

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

Last update: Pátková Vlasta (29.05.2018)
Learning resources -

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

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

Last update: Pátková Vlasta (29.05.2018)
Teaching methods -

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

Last update: Pátková Vlasta (29.05.2018)
Requirements to the exam -

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.

Last update: Pátková Vlasta (29.05.2018)
Syllabus -

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

Last update: Pátková Vlasta (29.05.2018)
Entry requirements -

none

Last update: Soušková Hana (12.06.2018)
Registration requirements -

none

Last update: Soušková Hana (12.06.2018)
Course completion requirements -

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

Last update: Pátková Vlasta (29.05.2018)
 
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