Subject description - BD5B37SAS
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Instructions
| BD5B37SAS | Signals and systems | ||
|---|---|---|---|
| Roles: | PV | Extent of teaching: | 14KP+6KC |
| Department: | 13137 | Language of teaching: | CS |
| Guarantors: | Fliegel K. | Completion: | Z,ZK |
| Lecturers: | Fliegel K., Puričer P. | Credits: | 4 |
| Tutors: | Fliegel K., Puričer P. | Semester: | L |
Web page:
https://moodle.fel.cvut.cz/courses/B2B37SAS/Anotation:
Introductory course focused on a description of continuous- and discrete-time signals and systems in time and frequency domains. The course also introduces the basic characteristics of bandpass signals, analog modulations and random signals.Course outlines:
| 1. | Introduction, classification of signals in continuous and discrete time, description and meaning (deterministic, random, causal, finite, periodic), special signals (unit step, rectangular pulse, Dirac impulse, unit impulse, sinc function). | |
| 2. | Characteristics of signals in time domain (average value, energy, power, mutual energy and power, cross-correlation and autocorrelation). | |
| 3. | Spectral representation of continuous signals, orthogonal signals, basis. Fourier Series (FS). Physical meaning of harmonic components. | |
| 4. | Fourier transform (FT). Properties of FT, Parseval's theorem. Transformation of special signals. Energy and power spectrum and their relation with correlation function. | |
| 5. | Spectrum of modulated signals, introduction to analog modulation. | |
| 6. | Spectrum of discrete signals. Sampling theorem. Discrete Fourier Series (DFS) and Discrete time Fourier Transform (DtFT). Energy and power spectral densities. | |
| 7. | Ideal sampling and interpolation, aliasing. | |
| 8. | Relations of FT, FS, DtFT and DFS. Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT) used for the calculation of FT and FS. | |
| 9. | Classification of systems and their properties, description of linear time-invariant (LTI) systems in time domain, convolution, stability of the system. | |
| 10. | Description of linear and time-invariant (LTI) system in the frequency domain, transfer function and frequency response. | |
| 11. | Ideal filters, replacement of a continuous-time system using a discrete one. | |
| 12. | Passage of signals through nonlinear systems, intermodulation. | |
| 13. | Bandpass signals and their description, complex envelope, sampling of bandpass signals. | |
| 14. | Introduction to random signals, stationarity and ergodicity, white noise. |
Exercises outline:
| 1. | Introduction and organization of the exercise. Review of required mathematical basics. Classification of signals in continuous and discrete-time. | |
| 2. | Characteristics of the signals in the time domain, signal energy and power in continuous and discrete-time. | |
| 3. | Characteristics of the signal in the time domain, autocorrelation and cross-correlation. | |
| 4. | Complex Fourier series (FS), spectrum of continuous periodic signals. | |
| 5. | First semester test. Power spectrum, relation to autocorrelation function. | |
| 6. | Fourier transform (FT), relationships signal - spectrum - autocorrelation function - energy/power spectral density. | |
| 7. | Fourier series and transformation of discrete-time signals DtFT and DtFS, relationships signal - spectrum - autocorrelation function - energy/power spectrum. | |
| 8. | Second semester test. Signal sampling. | |
| 9. | Classification of systems. Description of linear time-invariant (LTI) system in the time domain, convolution, stability. | |
| 10. | Description of linear time-invariant system (LTI) in frequency domain, transfer function and frequency response. | |
| 11. | Generation of basic signals, display, calculation of energy and power, calculation of autocorrelation function in Matlab. | |
| 12. | Calculation of the coefficients of Fourier series (FS and DtFS) and spectrum (FT and DtFT) using DFT/FFT, calculation of energy and power in the spectral domain in Matlab. | |
| 13. | LTI system, transfer function, poles and zeros, calculation of the response, characteristics of the input and output signals of the system in Matlab. | |
| 14. | Presentation of semester projects, assessment. |
Literature:
| [1] | Oppenheim, A. V., Willsky, A. S., Young, I. T., Signals and systems, Harlow: Pearson, 2013. | |
| [2] | Taylor, F. J., Principles of Signals and Systems, McGraw-Hill, 1994. | |
| [3] | Boulet, B., Fundamentals of Signals and Systems, Da Vinci Engineering Press, 2005. | |
| [4] | Papoulis, A., Probability, random variables, and stochastic processes, McGraw-Hill, 2002. | |
| [5] | Proakis, J. G., Salehi, M., Digital communications, Boston: McGraw - Hill, 2008. | |
| [6] | Hrdina, Z., Vejražka, F., Signály a soustavy, Praha: ČVUT, 1998. |
Requirements:
Knowledge of linear algebra and mathematical analysis, especially complex analysis and integral transforms.Keywords:
Signals, systems, signal processing, sampling, spectrum, Fourier transform. Subject is included into these academic programs:| Program | Branch | Role | Recommended semester |
| BKEEK_2016 | Common courses | PV | 4 |
| Page updated 21.12.2024 12:51:19, semester: Z,L/2024-5, Z/2025-6, Send comments about the content to the Administrators of the Academic Programs | Proposal and Realization: I. Halaška (K336), J. Novák (K336) |