CTU FEE Moodle

Ability to use of methods for signal analysis

1. Description of LTI systems in time and frequency domain. Linear convolution, stability, causality.
2. FIR filter design and analysis. Linear phase.
3. IIR filter design. Quantization and its consequences.
4. Introduction to spectral analysis. Types of Fourier transform and their properties.
5. Computation of cyclic convolution for long signals. OLA and OLS methods. Filtering in time domain.
6. Short time Fourier transform: time-frequency signal decomposition, spectrogram and uncertainty principle.
7. Oversampling, decimation and interpolation. Filter banks, wavelet transform.
8. Expected value, power, autocorrelation and their use for the biological signal processing.
9. Cross-correlation, cross spectral power density, coherence analysis.
10. Examples of detection and localization of rapid changes in biological signal.
11. Cumulative sum, match filtering, median filtering.
12. Linear prediction, parametric methods, basics of adaptive filtering, adaptive noise cancelation.
13. Relationship between discrete and time continuous systems. Discretization of time continuous systems, the choice of sampling period.
14. Reserved

1. LTI systems in time and frequency domain. Covolution, stability
2. FIR filter design
3. IIR filter design, quantization
4. Spectral analysis and DFT.
5. Cyclic convolution, zpracování Filtration in frequency domain
6. Short-time FT and wavelet transform
7. Resampling and filter banks.
8. Autocorrelation, mean and power of signals
9. Power spectral density, cross correlation and coherence
10. Median and matched filtering
11. Sudden changes detection
12. Liner prediction, adaptive filtering
13. Discretization of analog filters
14. Reserve

1. Tompinks, W. J.Biomedical Digital Signal Processing. Prentice-Hall, Inc., New Jersey, 1993.
2. Openheim, A.V., Shafer, R.W.: Discrete-Time Signal Processing. Prentice-Hall, Inc., New Jersey, 1998

Project, test and oral examination