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Last update: RNDr. Jiří Mírovský, Ph.D. (24.05.2021)
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Last update: RNDr. Jiří Mírovský, Ph.D. (24.05.2021)
To successfully finish the course, a student is required to attend the exercises (could miss up to 3 of them -- more is possible for extra homeworks) and pass the oral exam. |
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Last update: RNDr. Jiří Mírovský, Ph.D. (24.05.2021)
[1] R.W.Hamming. Digital Filters. Prentice-Hall, New Jersey, 1977 [2] Jiří Jan: Číslicová filtrace a restaurace signálů, VUTIUM, 2002 |
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Last update: RNDr. Jiří Mírovský, Ph.D. (24.05.2021)
Zkouska probiha ustne formou diskuse nad resenim zadaneho problemu, ktery lze vyresit s pouzitim nastroju uvedenych v syllabu. |
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Last update: RNDr. Jiří Mírovský, Ph.D. (24.05.2021)
(1) Discrete periodic signals. Discrete Fourier Transform and its properties (Parseval's theorem, convolution theorem). (2) FFT algorithm, fast multiplication of polynomials, fast convolution. (3) Fourier series and discrete non-periodic signals. (4) Operations with signals (modulation, convolution, non-linear distortion). (5) Linear Time-Invariant systems. Digital filters and their general form. IIR and FIR parts. Theorem on existence and uniqueness of digital filter solution. Invertibility, two-way filters. (6) Bode plot. Magnitude and phase. Phase delay, group delay, wave delay. (7) Implementing IIR filters (canonic forms). Round-off errors, stability and noise. (8) Minimum phase filters. Magnitude vs. group delay theorem. (9) Filter design methods. (10) Hilbert transform, analytic signal. (11) Sampling theorem, aliasing. Band-limited signals, Gibbs phenomenon. Resampling. A/D and D/A converters. Kell phenomenon. (12) Uncertainty principle and time-frequency representation. (13) Linear prediction (LPC). ASR front-ends. (14) Deconvolution, Wiener filter. Blind deconvolution. Echo suppression by temporal masking. (15) Frame of the vector space. Reconstruction theorem. (16) Signal restoration (denoising). (17) Biological sound processing: Human auditory system and pathways.
Exercises will have a form of practical application examples (e.g. equalizer, speaker location, principle of active and passive radar (sonar), signal restoration (denoising), etc.). These would be selected so as to exercise the theory just learned. |