SubjectsSubjects(version: 949)
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
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Level:  
For type: doctoral
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 -
Last update: Pátková Vlasta (29.05.2018)
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: Pátková Vlasta (29.05.2018)

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: Pátková Vlasta (29.05.2018)

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: Pátková Vlasta (29.05.2018)

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: Pátková Vlasta (29.05.2018)

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: Pátková Vlasta (29.05.2018)

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

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

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: Pátková Vlasta (29.05.2018)

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: Soušková Hana Ing. Ph.D. (12.06.2018)

none

Registration requirements -
Last update: Soušková Hana Ing. Ph.D. (12.06.2018)

none

Course completion requirements -
Last update: Pátková Vlasta (29.05.2018)

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

 
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