Digital Signal Processing

The course is a substitute for:

Digital Signal Processing (X31CZS)

Lecturer:

Tutor:

Supervisor:

Department of Circuit Theory

Synopsis:

The subject gives overview about basic methods of digital signal processing and their applications (examples from speech and biological signal processing): disrete-time signals and systems, signal characteristics in time and frequency domain, Fourier transform, fast algorithms for DFT computation, introduction to digital filter design, digital filtering in time and frequency domain, decimation and interpolation and their usage in filter banks, basics of LPC analysis. Seminars are devoted to the simple implementations and simulations of these methods in MATLAB. Above mentioned themes are explained on basic level, extended level is possible within individual projects.

Requirements:

Syllabus of lectures:

1. Introduction to DSP. Sampling theorem.

2. Basic characteristics of digital signals.

3. Autocorrelation and crosscorrelation functions

4. Fourier transform of discrete signal.

5. Properties of DFT, fast algorithms for DFT computation.

6. Spectral characteristics of stachastic and non-stationary signals.

7. Signal and system reprezentation in Z-domain

8. Digital Filtering I - FIR filters.

9. Digital filtering II - IIR filters.

10. Digital filtering in the frequency domain.

11. Basics of multi-band signal processing.

12. Basics of parametric methods of signal processing.

13. DSP applications in speech and biological signal processing. Signal compression.

14. Reserve.

Syllabus of tutorials:

1. Introduction to MATLAB and other tools

2. Simulation and analysis of digital systems in MATLAB

3. Implementation of linear and cyclic convolution in MATLAB

4. Some properties of DFT, interpolation, zero-padding

5. Filter design, structures implementation

6. Comb filter, complex resonator

7. Implementation of frequency sampling filters, Goertzel algorithm

8. Decimation and interpolation

9. Simulation of quantization effects in digital systems

10. Implementation of signal segmentation and averaging

11. Two methods of ZOOM techniques

12. Adaptive notch filter, frequency measurement

13. Implementation of correlation and spectral analysis methods

14. Project presentation, credit

Study Objective:

Study materials:

[1] Oppenheim, A.V., Shafer, R.W.: Discrete-Time Signal Processing. Prentice-Hall, Inc., New Jersey, 1998

[2] Rabiner, L.R., Schafer, F.W.: Digital Processing of Speech Signals. Prentice-Hall, Inc., New York, 1978

[3] Makhoul, J.: Linear Prediction: A Tutorial Review. In Proceedings of the IEEE, Vol. 63, No. 4, April 1975

[4] The MathWorks: MATLAB User's and Reference Guides.

[5] The MathWorks: Signal Processing Toolbox - User's Guide.

(Any other book devoted to digital signal processing.)

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Computer Science and Engineering (elective course)