Inhalt

[ 536DASCDSPV19 ] VL (*)Digital Signal Processing

Versionsauswahl
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
3 ECTS B3 - Bachelor 3. Jahr Artificial Intelligence Mario Huemer 2 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Bachelorstudium Artificial Intelligence 2025W
Lernergebnisse
Kompetenzen
(*)Students know and understand the fundamentals of both analog and discrete-time signals and systems including qualitative and mathematical aspects. They are able to utilize this knowledge to tackle fundamental signal processing problems.
Fertigkeiten Kenntnisse
(*)Students are able to

  • assess analog and discrete time systems with regards to basic system properties such as linearity, time-invariance, memory, … (K2, K3, K5),
  • plot signals in time- and frequency domain (K3, K6),
  • explain, apply, and derive the sampling theorem (K2, K5),
  • apply the convolution and correlation operations (K3),
  • derive the spectrum of a signal numerically with the help of the DFT and the FFT (K3, K6),
  • describe the behavior of discrete-time LTI systems in time- and frequency domain (K2, K3,K6),
  • analyze and design digital FIR and IIR filters (K3, K4, K6), and
  • apply the LMS adaptive filter algorithm (K2, K3).
(*)
  • Basics of Analog Systems Theory
  • Discrete Time Signals Fundamentals
  • Discrete Time LTI Systems Fundamentals
  • Fourier Transform of Discrete Time Signals (DTFT)
  • Sampling and Reconstruction
  • Correlation
  • Spectral Analysis of Discrete Time Signals (DFT, FFT, Short Time Fourier Transformation, Applications)
  • z-Transform
  • Digital Filters (FIR, IIR)
  • Vector/Matrix Representations of Discrete Time Signals and LTI Systems
  • Adaptive Filter Basics
Beurteilungskriterien (*)Written or oral exam (depending on the number of enrolled students).
Lehrmethoden (*)Lecture using slides and blackboard, Matlab based presentations.
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
Sonstige Informationen (*)This lecture and the accompanying exercise course form an inseparable didactic unit. The presented learning outcomes are achieved through the interaction of the lecture and the exercise course.
Äquivalenzen (*)521HARDDSVV13: VL Digitale Signalverarbeitung (3 ECTS)
Präsenzlehrveranstaltung
Teilungsziffer -
Zuteilungsverfahren Direktzuteilung