Signals and systems
Login to access the course.Signals and systems (Main course) A2B99SAS
Credits | 5 |
Semesters | Summer |
Completion | Assessment + Examination |
Language of teaching | Czech |
Extent of teaching | 2+2c |
Annotation
Course explains basic terms and methods for continuous-time and discrete-time signal and system analysis.
Study targets
Students will learn fundamental topics of signal processing for many areas like digital communication, measurements, acoustics, multimedia technology and other signal processing related specializations. the course gives explanation of basic terms used ti describe and analyze signals and systems in continuous and discrete time.
Course outlines
1. Types of signals, definition and sense (deterministic and stochastic -- introductory information).
2. Signal characteristics (average, energy, power, mutual energy, correlation).
3. Spectral representation of continuous and discrete signals.
4. Relation between transformations and their implications.
5. Spectral density and its relation to correlation function. Parseval theorem.
6. Systems classification and characteristic, definition of systems in time domain, convolution.
7. Continuous and discrete time systems definition, transfer function and frequency response.
8. Ideal signal sampling and interpolation. Spectral overlap, continuous and discrete time systems relation.
9. Bandpass signals and their definition, complex envelope.
10. Bandpass signals envelope and phase, sampling of baseband signals.
11. Introduction to modulation, AWGN, SNR.
12. Representative types of analog and digital modulation.
13. Signal pass through non-linear systems, intermodulation.
14. Selected applications.
2. Signal characteristics (average, energy, power, mutual energy, correlation).
3. Spectral representation of continuous and discrete signals.
4. Relation between transformations and their implications.
5. Spectral density and its relation to correlation function. Parseval theorem.
6. Systems classification and characteristic, definition of systems in time domain, convolution.
7. Continuous and discrete time systems definition, transfer function and frequency response.
8. Ideal signal sampling and interpolation. Spectral overlap, continuous and discrete time systems relation.
9. Bandpass signals and their definition, complex envelope.
10. Bandpass signals envelope and phase, sampling of baseband signals.
11. Introduction to modulation, AWGN, SNR.
12. Representative types of analog and digital modulation.
13. Signal pass through non-linear systems, intermodulation.
14. Selected applications.
Exercises outlines
1. Introduction, signal definition, signal analysis methods.
2. Signal characteristic determination - average, energy, correlation function.
3. Spectral analysis of periodical signals via Fourier series.
4. Spectral analyses of non-periodical signals, Fourier transform application.
5. DFT performance and usage, multitone signal analysis.
6. Transit of signal through linear time invariant system, transient states.
7. System stability, continuous and discrete time system relation.
8. System in time and frequency domains, system characteristics.
9. System modelling in discrete time.
10. Signal sampling and resampling, spectral overlay.
11. Baseband and bandpass signal relation, frequency conversion, sampling.
12. Bandpass signal processing, representative modulations.
13. Non-linear bandpass system modelling and analysis (example: mixer, envelope detector).
14. Semestral results summarize, examination of works.
2. Signal characteristic determination - average, energy, correlation function.
3. Spectral analysis of periodical signals via Fourier series.
4. Spectral analyses of non-periodical signals, Fourier transform application.
5. DFT performance and usage, multitone signal analysis.
6. Transit of signal through linear time invariant system, transient states.
7. System stability, continuous and discrete time system relation.
8. System in time and frequency domains, system characteristics.
9. System modelling in discrete time.
10. Signal sampling and resampling, spectral overlay.
11. Baseband and bandpass signal relation, frequency conversion, sampling.
12. Bandpass signal processing, representative modulations.
13. Non-linear bandpass system modelling and analysis (example: mixer, envelope detector).
14. Semestral results summarize, examination of works.
Literature
A. V. Oppenheim, A. S. Wilsky with S.H. Nawab: Signals and Systems. Prentice-Hall, Second Edition, 1997.
J. R. Buck, M. M. Daniel, A. C. Winter: Computer Explorations in Signals and Systems Using MATLAB. Prentice-Hall, 1997.
Taylor, F.J.: Principles of signals and systems. McGraw-Hill, 1994.
Narasimhan, S.V., Veena, S: Signal Processing, principles and implementation. Alpha Science International, Harrow, 2005.
Proakis, J.G.: Digital Communications. McGraw-Hill, 2001.
J. R. Buck, M. M. Daniel, A. C. Winter: Computer Explorations in Signals and Systems Using MATLAB. Prentice-Hall, 1997.
Taylor, F.J.: Principles of signals and systems. McGraw-Hill, 1994.
Narasimhan, S.V., Veena, S: Signal Processing, principles and implementation. Alpha Science International, Harrow, 2005.
Proakis, J.G.: Digital Communications. McGraw-Hill, 2001.
Requirements
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http://moodle.kme.feld.cvut.cz/
http://moodle.kme.feld.cvut.cz/