|
Lecturer(s)
|
-
Holada Miroslav, Ing. Ph.D.
|
|
Course content
|
Lectures 1. Signal as source of information. Examples of various signals. Computer processing of signals. 2. Digital signals: their origin, description in time domain. AD and DA conversion. 3. Digital signals: basic types of signal, basic signal operations. Signal parameters. 4. Signals in frequency domain. Fourier series. 5. Sampling, Nyqist theorem, aliasing, signal reconstruction. 6. Relation between signals and systems. LTI systems and their properties. 7. Digital LTI systems, convolution, simple filters. 8. Frequency analysis of digital signals. Amplitude and phase spectrum. 9. Discrete Fourier transform, FFT. 10. FIR filters and their design. 11. Filter anlaysis by Z-transform, IIR filters. 12. Modulation - AM, FM, PM. 13. Correlation and autocorrelation function. Measuring similarity between signals. 14. Demonstrations of some advanced signal processing systems. Practice 1. Introduction to MATLAB. 2. Signals in MATLAB: methods of displaying and replaying. 3. Basic signal processing procedures. 4. Fourier analysis in MATLAB. 5. Sampling, application of Nyquist theorem, practical aspects of aliasing. 6. Difference equations, function Filter in MATLAB. 7. Convolution in MATLAB. 8. Frequency analysis Filter in MATLAB. 9. Implementation of DFT in MATLAB 10. Design and application of FIR filters 11. IIR filters. 12. AM and FM systems. 13. Correlation and autocorrelation function 14. Summary.
|
|
Learning activities and teaching methods
|
Monological explanation (lecture, presentation,briefing), Laboratory work
- Class attendance
- 56 hours per semester
- Home preparation for classes
- 50 hours per semester
- Preparation for exam
- 44 hours per semester
|
|
Learning outcomes
|
The subject provides an introduction to basic methods of signal processing. Although analog signals are also mentioned, the main focus is given to digital signals and digital signal processing systems. The subject includes the following topics: time domain and frequency domain analysis, convolution, correlation, FFT, filter design, modulation. In excercises, students use MATLAB to solve such tasks like, acoustic signal filtering, music tone generation, correlation analysis, picture enhancement, etc.
Theoretic piece of knowledge and practical skills from requered areas
|
|
Prerequisites
|
Condition of registration: basic knowledge mathematics taught in 1st and 2nd semester
|
|
Assessment methods and criteria
|
Combined examination, Written exam
Requirements for obtaing the credit are activity at the practicals /seminars and successful passing of the tests. Examination has form a written test.
|
|
Recommended literature
|
-
McClellan J.H., Schafer R., Yoder M.A. DSP First - A Multimedia Approach. Prentice Hall, 1998..
|