CTU FEE Moodle
Signals and systems
B232 - Summer 23/24
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Signals and systems - B3B31SAS
| Credits | 5 |
| Semesters | Winter |
| Completion | Assessment + Examination |
| Language of teaching | Czech |
| Extent of teaching | 2P+2C |
Annotation
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
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 outlines
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
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
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