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Lecturer(s)
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Zálabský Tomáš, Ing. Ph.D.
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Filip Aleš, doc. Ing. CSc.
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Juryca Karel, Ing. Ph.D.
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Pidanič Jan, doc. 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 11. Laplace transform: definition, properties, region of convergence 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), Work with text (with textbook, with book), Methods of individual activities, 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 signals, electronic circuits and modulations gained during the study.
Student will be able to work with Fourier transform, Laplace, Z-transform, discrete Fourier transform, A/D conversion. He (she) will be able to use this knowledge for realization of concrete digital signal processing equipment.
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Prerequisites
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Mathematics (integral, derivation, function, series, etc.)
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Assessment methods and criteria
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Oral examination, Written examination, Home assignment evaluation
Study includes also an individual work on digital signal processing task.
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Recommended literature
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Antoniou A. Digital signal processing. McGraw: Hill, 2005.
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Hayes M.H. Digital signal processing. McGraw: Hill, 1999.
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Smith S.W. Digital signal processing. California Technical Publishing, 1999.
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Zelniker, G., Taylor, F.J. Advanced digital signal processing. New York: Marcel Dekker, 1994.
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