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Explanatory Notes
Instructions
Web page:
https://moodle.fel.cvut.cz/courses/B3B31SAS
Anotation:
The course focuses on explaining basic terms used for the description and analysis of determined signals and systems (including filters) in continuous- and discrete-time. The graduate will acquire a basic overview of the issues and learn how to work with concepts, perform simple analysis of systems and signals, and interpret and discuss the results.
Study targets:
Become familiar with the basic concepts and learn how to use MATLAB for analysis and design of systems and for signal processing.
Course outlines:
1. | | Continuous- and discrete-time signals and systems. Cross-energy and correlation |
2. | | LTI system representation in the time domain, convolution |
3. | | Representation of LTI systems in the frequency domain, frequency response |
4. | | Transfer function of continuous-time systems, poles and zeros, the relationship between time and frequency domain, ideal integrator and differentiator |
5. | | Bode and Nyquist frequency plot, asymptotic Bode plot |
6. | | Stability, feedback, gain and phase margins |
7. | | Relationship between transfer function and state-space representation of LTI continuous-time systems, asymptotic and BIBO stability |
8. | | Nonlinear systems and their linearization for small signals |
9. | | Sampling and reconstruction of signals, representation in time and frequency domain |
10. | | Methods for discretization of continuous-time systems |
11. | | Introduction to analog filters, types and properties of approximations |
12. | | Digital filters: types, characteristics, design, examples of 1-D and 2-D, filter simulation, quantization and its consequences |
13. | | Application of digital filtering for noise reduction and signal restoration of signals, modulations |
14. | | Reserve |
Exercises outline:
1. | | Continuous- and discrete-time signals and their generation in MATLAB |
2. | | System simulation in Simulink |
3. | | The use of Fourier transform and the Fourier series, frequency respons |
4. | | Transfer function, stability, types of system interconnections |
5. | | Bode and Nyquist frequency plot, laboratory measurement |
6. | | Measurement of frequency response, gain and phase margins |
7. | | Relationship between transfer function and state-space representation |
8. | | Examples of system linearization for small signal |
9. | | Signal sampling and reconstruction |
10. | | Methods of system discretization |
11. | | The tools for the design of analog filters, laboratory measurement on SC filters |
12. | | Design and simulation of digital filters IIR and FIR filters |
13. | | Examples of simple methods for noise reduction, examples of modulations |
14. | | Reserve |
Literature:
1. | | V. Oppenheim, G. C. Verghese: Signals, Systems and Inference. Prentice Hall 2015, ISBN-13: 978-0133943283 |
2. | | Hwei P. Hsu: Signals and systems. McGraw-Hill, 2013, ISBN: 978-0071829465 |
Requirements:
Knowledge of the concepts and methods of mathematical analysis, Fourier and Laplace transforms and z-transform, solution of linear differential equations with constant coefficients, basic knowledge of physics
Keywords:
linear time-invariant systems, frequency response, transfer function, stability, feedback, linearization of systems, state-space representation of the system, convolution, correlation, spectrum, analog and digital filters, discretization of signals and systems
Subject is included into these academic programs:
Page updated 9.11.2024 15:51:53, semester: L/2024-5, L/2023-4, Z/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) |