CTU FEE Moodle

To deepen students' theoretical knowledge of mathematics in the field of signal processing and to acquire knowledge for the design of FIR and IIR filters, implementation methods including implementation of filter banks.

1. Overview of signals discrete in time in time domain and in frequency domain
2. Transforms with finite support (DFT, DCT)
3. Z transform
4. Linear time invariant systems discrete in time in domain and in transformed domain
5. Structures of digital filters
6. Design of FIR filters, advanced approximations
7. Design of IIR filters
8. Sampling of 2D Signals
9. 2-D and m-D transforms
10. Design of 2-D and m-D digital filters
11. Finite word length, analysis
12. Basics of multirate digital signal processing
13. Multirate filter banks and wavelets
14. Spectral analysis, windows

1. Matlab - creation of m-files, generation of signals, analysis of simple digital structures, visualization in the time domain.
2. Examples from the field of discrete signals and systems in the time domain.
3. Examples of calculation of Fourier transformation using Matlab., calculation of frequency response and phase, generation of signals, their visualization.
4. Convolution, deconvolution, system response.
5. Factorization of FIR and IIR transfer functions, parallel implementation, cascade implementation.
6. Systems with finite word length, calculation examples, applications.
7. Design of digital FIR filters using Matlab, window function.
8. Design of 1D and 2D systems. Sampling, interpolation and decimation of signals.
9. IIR filter design using Matlab, approximation, stability.
10. 1D and 2D FIR filter design
11. Multirate Digital Signal Processing – design and implementation, resampling.
12. Multirate Digital Signal Processing.
13. Credit test.

1. Sanjit K. Mitra, Digital Signal Processing, 4th Edition, McGraw-Hill, 2010
2. Boaz Porat: A course in Digital signal processing, John Wiley 1997

Knowledge from lectures, 100% participation in exercises, successful completion of the test.