Inhalt

[ 536DASCDSPU19 ] UE (*)Digital Signal Processing

Versionsauswahl
Es ist eine neuere Version 2022W dieser LV im Curriculum Bachelorstudium Maschinenbau 2022W vorhanden.
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
1,5 ECTS B3 - Bachelor 3. Jahr Informatik Mario Huemer 1 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Bachelorstudium Artificial Intelligence 2019W
Ziele (*)Digital signal processing nowadays is present in almost every consumer electronics device, vehicle, industrial machinery, et cetera. This lecture provides an introduction in the field of digital signal processing. Main topics are discrete-time signals and linear time-invariant systems, their representations and mathematical treatment in the time and frequency domain. Furthermore, important signal transforms like wavelet transforms and the discrete cosine transform are discussed.
Lehrinhalte (*)
  • Analog Signals and Systems (Introduction incl. Fourier transform)
  • Sampling, Sampling Theorem
  • Discrete Time Signals
    • Important Signals
    • Correlation
    • Spectral Representation of Discrete Time Signals: DTFT, DFT, FFT, Short time Fourier transform
  • Digital Filters: Analysis and Design of FIR and IIR Filters
  • Further Signal Transforms
    • Wavelet Transform
    • Discrete Cosine Transform
  • Time-Frequency-Distributions
Beurteilungskriterien (*)Homework to be uploaded and evaluated
Lehrmethoden (*)
  • Demonstration of examples
  • Matlab examples
  • Homework
Abhaltungssprache Englisch
Literatur (*)
  • Lecture Slides
  • Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing: Pearson New International Edition, Pearson Education Limited 2014.
Lehrinhalte wechselnd? Nein
Präsenzlehrveranstaltung
Teilungsziffer 35
Zuteilungsverfahren Direktzuteilung