phy605 - Digital Signal Processing (Vollständige Modulbeschreibung)

phy605 - Digital Signal Processing (Vollständige Modulbeschreibung)

Originalfassung Englisch PDF Download
Modulbezeichnung Digital Signal Processing
Modulkürzel phy605
Kreditpunkte 6.0 KP
Workload 180 h
(
Attendance: 56 hrs, Self study: 124 hrs
)
Einrichtungsverzeichnis Institut für Physik
Verwendbarkeit des Moduls
  • Master Engineering Physics (Master) > Schwerpunkt: Acoustics
Zuständige Personen
  • Doclo, Simon (Modulverantwortung)
  • Doclo, Simon (Prüfungsberechtigt)
Teilnahmevoraussetzungen
Basic knowledge about continuous-time signals and systems and statistics. In addition, Matlab programming skills are required.
Kompetenzziele
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
Modulinhalte
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
Unterrichtsprachen Deutsch, Englisch
Dauer in Semestern 1 Semester
Angebotsrhythmus Modul
Aufnahmekapazität Modul unbegrenzt
Modulart Wahlpflicht / Elective
Modullevel MM (Mastermodul / Master module)
Lehr-/Lernform Lecture: 2hrs/week; Exersise: 2hrs/week
Vorkenntnisse Basic knowledge about continuous-time signals and systems and statistics. In addition, Matlab programming skills are required.
Prüfung Prüfungszeiten Prüfungsform
Gesamtmodul
written exam (max. 3 hours) or 30 minutes oral exam
Lehrveranstaltungsform Vorlesung
SWS 4
Angebotsrhythmus SoSe oder WiSe