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FEKT-NMZSAcad. year: 2011/2012
Linear, particularly multi-rate filters. Non-linear filtering - polynomial and ranking filters, homomorphic filtering anddeconvolution, non-linear matched filters. Identification of stochastic signals. Formalised optimum signal restoration in unified view: Wiener filter in generalised discrete formulation, Kalman filtering and signal restoration, source modelling and further approaches. Adaptive filtering and identification, algorithms of adaptation, classification of typical adaptive filtering applications. Signal processing by neural networks. Typical concrete applications of the above methods.
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Offered to foreign students
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Specification of controlled education, way of implementation and compensation for absences
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branch MN-TIT , 1 year of study, summer semester, elective specialisedbranch MN-EST , 1 year of study, summer semester, elective specialisedbranch MN-BEI , 1 year of study, summer semester, elective specialised
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Exercise in computer lab