[ 521HARDDSVU13 ] UE Digital signal processing

(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
1,5 ECTS B3 - Bachelor's programme 3. year Computer Science Mario Huemer 1 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Computer Science 2022W
Objectives Students know and understand the basic mathematical methods for describing analog and discrete time signals as well as linear, time-invariant systems. Students are able to design digital filters with the help of (e.g. Matlab based) design tools. They are able to program and apply the basic digital signal processing algorithms (e.g. FFT, convolution, FIR and IIR filtering, correlation).
  • Characterization of signals
  • Spectral representation of analog signals
  • Sampling and reconstruction, Sampling theorem
  • Spectral representation of discrete time signals (discrete time Fourier transform, DFT, FFT and applications)
  • Discrete time systems
  • Design of digital filters (FIR, IIR)
  • Correlation and applications
  • Time-Frequency-Analysis
  • Further topics in signal processing
Criteria for evaluation Assessment of bi-weekly analytic and Matlab-programming exercises.
Methods The contents of the lecture is deepened by examples and Matlab-simulations. By working on bi-weekly analytic examples and Matlab-programming assignments, which are discussed after submission, students acquire the skills to program and apply the basic digital signal processing algorithms (e.g. FFT, convolution, FIR and IIR filtering).
Language German
Study material Lecture slides

Recommended reading:

  • Daniel von Gr√ľnigen, Digitale Signalverarbeitung, 4. Auflage, Fachbuchverlag Leipzig im Carl Hanser Verlag, 2008.
  • Ken Steiglitz, A Digital Signal Processing Primer, Addison-Wesley Publishing Company, 1995.
Changing subject? No
Further information
Corresponding lecture (*)INBIPUECAR2: UE Computer Architecture 2 (1,5 ECTS) bzw. INBIPUEARC2: UE Rechnerarchitektur 2 (1,5 ECTS) bzw. INBVCUEPARR: UE Parallele Rechner (1,5 ECTS)
On-site course
Maximum number of participants 35
Assignment procedure Direct assignment