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

In the frame of computational laboratories it is necessary to evaluate 3 projects including mathematical analysis of methods used and their verification in the MATLAB/Simulink environment. During exam the knowledge of mathematical metods of signal and image analysis and processing is verified together with their algorithmic implementation (http://uprt.vscht.cz/prochazka/pedag/ATHENSe.htm).

[1] T. Bose: Digital Signal and Image Processing, Wiley, 2004

[2] Vaseghi S.V.: Multimedia Signal Processing, Wiley, 2007.

[3] http://uprt.vscht.cz/prochazka/pedag/DSPc.htm

In the frame of computational laboratories it is necessary to evaluate 3 projects including mathematical analysis of methods used and their verification in the MATLAB/Simulink environment. During exam the knowledge of mathematical metods of signal and image analysis and processing is verified together with their algorithmic implementation (http://uprt.vscht.cz/prochazka/pedag/ATHENSe.htm).

1. Algorithmic tools of digital signal processing, fundamentals of MATLAB environment

2. Numerical, symbolic and visualization tools of MATLAB, data files processing

3. Time-domain signal representation, difference equations, selected statistical methods

4. Frequency-domain signal analysis, sampling, discrete Fourier transform, decomposition

5. Spectrum estimation, aliasing, short-time Fourier transform, window functions

6. Z-transform and system description, discrete transfer function, frequency transfer function

7. Digital filters, basic methods in the time domain, convolution, FIR filters, filter banks

8. IIR filters, basic properties, signal decimation

9. Filtering methods in frequency domain, signal reconstruction, window functions

10. Linear methods of time series modelling and prediction, SVD a QR algorthm, model selection

11. Nonlinear methods of signal processing, median filters, principles of neural networks

12. Basic methods of image analysis, 2D Fourier transform, image processing

13. Signal processing in engineering, signal prediction, Simulink environment, basic blocks

14. Biomedical signal and image processing

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

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