CTU FEE Moodle
Signal Processors in Practice
B232 - Summer 23/24
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Signal Processors in Practice - A0M38SPP
| Credits | 5 |
| Semesters | Both |
| Completion | Assessment + Examination |
| Language of teaching | Czech |
| Extent of teaching | 2+2L |
Annotation
Basic architecture of digital signal processors, main features and
properties, description of important processor blocks (ALU, MAC).
Development and supporting tools for design and debug. Fundamental method of
digital signal processing including practise implementation on digital
signal processor (DSP). Demonstration of HW design with application of DSP.
Within laboratory exercises, realisation of scheduled or own complex
project.
properties, description of important processor blocks (ALU, MAC).
Development and supporting tools for design and debug. Fundamental method of
digital signal processing including practise implementation on digital
signal processor (DSP). Demonstration of HW design with application of DSP.
Within laboratory exercises, realisation of scheduled or own complex
project.
Study targets
No data.
Course outlines
1. Basic architecture of digital signal processors (DSP), main features,
typical application in practice, overview of leading-edge manufactures of
DSP.
2. Internal layout, computational units ALU, MAC, instruction counter,
method of addressing, address memory range.
3. Algorithm of direct digital synthesis (DDS) and its implementation on
DSP.
4. Algorithm of digital filters (FIR a IIR) , design in MATLAB program.
5. Adaptive filtering, LMS algorithm.
6. Algorithm of FFT, computation method of FFT on DSP.
7. Correlation and autocorrelation method.
8. Oversampling of signals, decimation and interpolation.
9. Numeric formats used for data representation in memory (integer,
fractional), saturation. arithmetic, influence of quantization on
computation accuracy.
10. DSP peripheries - serial port, timers, DMA, multiprocessor
communication.
11. Development and supporting tools for design and debugging.
12. Demonstration of HW design with application of DSP.
13. Application of DSP in audio-video signal processing (MP3, MPEG4 format),multiprocessor systems.
typical application in practice, overview of leading-edge manufactures of
DSP.
2. Internal layout, computational units ALU, MAC, instruction counter,
method of addressing, address memory range.
3. Algorithm of direct digital synthesis (DDS) and its implementation on
DSP.
4. Algorithm of digital filters (FIR a IIR) , design in MATLAB program.
5. Adaptive filtering, LMS algorithm.
6. Algorithm of FFT, computation method of FFT on DSP.
7. Correlation and autocorrelation method.
8. Oversampling of signals, decimation and interpolation.
9. Numeric formats used for data representation in memory (integer,
fractional), saturation. arithmetic, influence of quantization on
computation accuracy.
10. DSP peripheries - serial port, timers, DMA, multiprocessor
communication.
11. Development and supporting tools for design and debugging.
12. Demonstration of HW design with application of DSP.
13. Application of DSP in audio-video signal processing (MP3, MPEG4 format),multiprocessor systems.
Exercises outlines
1. Introduction exercise - SW a HW debugging equipment, supporting tools.
2. Instruction set of ADSP21XX, example of writing program code in assembler
and language C.
3. Design and implementation of DDS algorithm.
4. Design of FIR filter by means of MATLAB program, implementation on DPS.
5. Design of IIR filter by means of MATLAB program, implementation on DPS.
6. Design and DSP implementation of DFT algorithm.
7. Implementation of correlation and autocorrelation method.
8. Semester project.
9. Semester project.
10. Semester project.
11. Semester project.
12. Semester project.
13. Project evaluation, assessment.
2. Instruction set of ADSP21XX, example of writing program code in assembler
and language C.
3. Design and implementation of DDS algorithm.
4. Design of FIR filter by means of MATLAB program, implementation on DPS.
5. Design of IIR filter by means of MATLAB program, implementation on DPS.
6. Design and DSP implementation of DFT algorithm.
7. Implementation of correlation and autocorrelation method.
8. Semester project.
9. Semester project.
10. Semester project.
11. Semester project.
12. Semester project.
13. Project evaluation, assessment.
Literature
[1] B.A. Shenoi: Introduction to digital signal processing and filter design. Wiley. 2005
[2] Mixed-signal and DSP Design Techniques. Norwood. Analog Devices, 2000.
[3] Digital signal processing: [principles, algorithms, and applications]. John G. Proakis, Dimitris G. Manolakis. Prentice Hall, 2007.
[2] Mixed-signal and DSP Design Techniques. Norwood. Analog Devices, 2000.
[3] Digital signal processing: [principles, algorithms, and applications]. John G. Proakis, Dimitris G. Manolakis. Prentice Hall, 2007.
Requirements
No data.