CTU FEE Moodle
Digital Signal Processing in Telecommunication
B232 - Summer 23/24
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Digital Signal Processing in Telecommunication - B2M32DZS
| Credits | 5 |
| Semesters | Winter |
| Completion | Assessment + Examination |
| Language of teaching | Czech |
| Extent of teaching | 2P + 2L |
Annotation
The goal of the subject is to make familiar with theory, methods and implementation of algorithms of the digital signal processing of one- and multi-dimensional signals related to the telecommunication technology.
Study targets
The aim of the study is to acquire the knowledge in theory, methods and implementation of algorithms of the digital signal processing of one- and multi-dimensional signals related to the telecommunication technology.
Course outlines
1. Sampling of continuous analog signals and their digitization
2. Integral transforms and their discrete counterparts
3. Decimation and interpolation, general sample rate conversion
4. Design of FIR filters
5. Design of IIR filters
6. Design of optimal FIR filters, narrow-band filters, comb filters, finite word length
7. Adaptive filtering, echo attenuation
8. Compression of acoustic signals
9. 2-D and n-D signals and systems
10. Design of 2-D FIR filters, separable, non-separable
11. Image compression
12. Video compression
13. Implementation of DSP algorithms
14. Architectures of digital signal processors
2. Integral transforms and their discrete counterparts
3. Decimation and interpolation, general sample rate conversion
4. Design of FIR filters
5. Design of IIR filters
6. Design of optimal FIR filters, narrow-band filters, comb filters, finite word length
7. Adaptive filtering, echo attenuation
8. Compression of acoustic signals
9. 2-D and n-D signals and systems
10. Design of 2-D FIR filters, separable, non-separable
11. Image compression
12. Video compression
13. Implementation of DSP algorithms
14. Architectures of digital signal processors
Exercises outlines
1. Matlab - Sampling of continuous analog signals and their digitization
2. Matlab - CTFT, DTFT, DFT, FFT, KLT
3. Matlab - Decimation and interpolation, general sample rate conversion
4. Matlab - Design of FIR filters
5. Matlab - Design of IIR filters
6. Matlab - Design of optimal FIR filters, narrow-band filters, comb filters, finite word length
7. Matlab - Adaptive filtering, echo attenuation
8. Matlab - Compression of acoustic signals
9. Matlab - 2-D and n-D signals and systems
10. Matlab -Design of 2-D FIR filters, separable, non-separable
11. Matlab -Image compression
12. Matlab -Video compression
13. DSP C6x - Implementation of DSP algorithms
14. DSP C6x - Implementation of DSP algorithms-cont.
2. Matlab - CTFT, DTFT, DFT, FFT, KLT
3. Matlab - Decimation and interpolation, general sample rate conversion
4. Matlab - Design of FIR filters
5. Matlab - Design of IIR filters
6. Matlab - Design of optimal FIR filters, narrow-band filters, comb filters, finite word length
7. Matlab - Adaptive filtering, echo attenuation
8. Matlab - Compression of acoustic signals
9. Matlab - 2-D and n-D signals and systems
10. Matlab -Design of 2-D FIR filters, separable, non-separable
11. Matlab -Image compression
12. Matlab -Video compression
13. DSP C6x - Implementation of DSP algorithms
14. DSP C6x - Implementation of DSP algorithms-cont.
Literature
[1] James H. McClellan, Ronald W. Schafer, Mark A. Yoder, Signal Processing First, Prentice Hall, 2003.
[2] Sanjit K. Mitra, Digital Signal Processing, 4th Edition, McGraw-Hill, 2010.
[3] Rulph Chassaing, Donald S. Reay, Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK, 2nd Edition, John Wiley, 2008.
[4] Proprietary Materials for Lectures and Seminars
[2] Sanjit K. Mitra, Digital Signal Processing, 4th Edition, McGraw-Hill, 2010.
[3] Rulph Chassaing, Donald S. Reay, Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK, 2nd Edition, John Wiley, 2008.
[4] Proprietary Materials for Lectures and Seminars
Requirements
Solid knowledge of the basics in the digital signal processing, advantageously in the extent of [1].