Inhalt

[ 536DASCDSPV19 ] VL Digital Signal Processing

Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS B3 - Bachelor's programme 3. year (*)Artificial Intelligence Mario Huemer 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Artificial Intelligence 2025W
Learning Outcomes
Competences
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.
Skills Knowledge
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
Criteria for evaluation Written or oral exam (depending on the number of enrolled students).
Methods Lecture using slides and blackboard, Matlab based presentations.
Language English
Study material
  • Lecture Slides
  • Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing: Pearson New International Edition, Pearson Education Limited 2014.
Changing subject? No
Further information 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.
Corresponding lecture 521HARDDSVV13: VL Digitale Signalverarbeitung (3 ECTS)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment