Signal Processors in Practice

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Measurement

Synopsis:

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.

Requirements:

Syllabus of lectures:

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.

Syllabus of tutorials:

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.

Study Objective:

Study materials:

[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.

Note:

Further information:

http://measure.feld.cvut.cz/en/education/courses/AE0M38SPP

No time-table has been prepared for this course

The course is a part of the following study plans: