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Lecturer(s)
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Pidanič Jan, doc. Ing. Ph.D.
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Juryca Karel, Ing. Ph.D.
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Course content
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1. Analog signals: signal operations, representation and modeling, Basic building blocks for continuous-time signals 2. Signal classification: Periodical signals, non-periodical signals, causal and non-causal signals, signals in the continuous and discrete time. Basic signal characteristics: mean value, power, energy, correlation function. Signal decomposition. 3. Discrete signals: signal operations, representation and modeling, Basic building blocks for discrete-time signals. Signal decomposition. 4. Analyzing Continuous-Time Systems in the Time Domain: properties, classification, block Diagram Representation of Continuous-Time Systems 5. Analyzing Continuous-Time Systems in the Time Domain II.: differential equations for Continuous-Time System, solving of differential equation, impulse response and convolution 6. Analyzing Discrete-Time Systems in the Time Domain: properties, classification, block Diagram Representation of Continuous-Time Systems, difference Equations for Continuous-Time System 7. Analyzing Discrete-Time Systems in the Time Domain II.: difference equations for Discrete-Time System, solving of difference equation, impulse response and convolution 8. Fourier Analysis for periodic Continuous-Time Signals and Systems: goniometric, polar and complex Fourier series, properties 9. Fourier Analysis for non-periodic Continuous-Time Signals and Systems: Fourier transform, properties 10. Fourier Analysis for periodic/non-periodic Discrete-Time Signals and Systems, properties, tools I. 11. Fourier Analysis for periodic/non-periodic Discrete-Time Signals and Systems, properties, tools II. 12. Z-transform: definition, properties, region of convergence 13. Sampling and Reconstruction: theoretical and practical sampling, quantization
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Laboratory work
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Learning outcomes
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The aim of the subject is to provide students with theoretical backgrounds of signals processing needed for the further study of signal processing in communication and control. The subject links to basic knowledge of continuous/discrete signals and systems, analyzing tools in time/frequency domain for continuous/discrete signals, Laplace and z-transform. The last part is dedicated to sampling and reconstruction of signals (A/D and D/A conversion).
Student will be able to work with Fourier transform, Laplace, Z-transform, discrete Fourier transform, A/D conversion
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Prerequisites
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Knowledge of mathematics in the scope of the first two years of bachelor's study, as complex numbers, arithmetic / trigonometric series. Knowledge of working in the Matlab environment.
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Assessment methods and criteria
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Oral examination, Written examination
Basic skills: mathematics (integral, derivation, function, series, etc.). Knowledge of Matlab environment.
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Recommended literature
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Davídek, V., Sovka, P. Číslicové zpracování signálu a implementace. ČVUT.
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PRCHAL, J., ŠIMÁK, B. Digitální zpracování signálů v telekomunikacích. Praha: ČVUT, 2000.
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Uhlíř J., Sovka P. Číslicové zpracování signálu a informací, Skripta ČVUT.
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