phy605 - Digital Signal Processing
Module label | Digital Signal Processing |
Modulkürzel | phy605 |
Credit points | 6.0 KP |
Workload | 180 h
( Attendance: 56 hrs, Self study: 124 hrs )
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Institute directory | Institute of Physics |
Verwendbarkeit des Moduls |
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Zuständige Personen |
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Prerequisites | |
Skills to be acquired in this module | The students acquire knowledge about theoretical concepts and methods of signal processing and system theory for discrete-time signals and systems. The students are able to apply these theoretical concepts and methods in analytical, numerical and programming exercises. |
Module contents | System properties (stability, linearity, time-invariance, causality); Discrete-time signal processing: sampling theorem, time-domain analysis (impulse response, convolution), z-transform, frequency-domain analysis (transfer function, discrete-time Fourier transform, discrete Fourier transform, FFT, STFT), digital filter design (FIR, IIR, linear phase filter, all-pass filter, signal flow graph), multi-rate signal processing (down/up-sampling, filter banks); Statistical signal processing: stationarity, ergodicity, correlation, Wiener-Khinchin theorem, spectral estimation; Adaptive filters: optimal filters, Wiener filter, time-domain algorithms (RLS, NLMS), frequency-domain algorithms (FDAF);Matlab exercises about discrete-time signal processing and adaptive filters. |
Literaturempfehlungen | A. V. Oppenheim, R. W. Schafer, “Discrete-Time Signal Processing”, Prentice Hall, 2013. J. G. Proakis, D. G. Manolakis, “Digital Signal Processing – Principles, Algorithms and Applications”, Prentice Hall, 2013. S. Haykin, ”Adaptive Filter Theory“, Pearson, 2013. P. P. Vaidyanathan, ”Multirate systems and filter banks“, Prentice Hall, 1993. K.-D. Kammeyer, K. Kroschel, ”Digitale Signalverarbeitung: Filterung und Spektralanalyse mit MATLAB Übungen“, Broschiert, 2018 |
Links | |
Languages of instruction | German, English |
Duration (semesters) | 1 Semester |
Module frequency | |
Module capacity | unlimited |
Teaching/Learning method | Vorlesung: 2 SWS, Übung: 2 SWS |
Previous knowledge | Basic knowledge about continuous-time signals and systems and statistics. In addition, Matlab programming skills are required. |
Examination | Prüfungszeiten | Type of examination |
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Final exam of module | Max. 180 min. Klausur oder 30 min. mündliche Prüfung |
Lehrveranstaltungsform | Lecture |
SWS | 4 |
Frequency | SoSe oder WiSe |
Workload Präsenzzeit | 56 h |