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Innovative Metrology 2017

Rückblick: Innovation Messtechnik 2015

22nd IMEKO TC2 Symposium on Photonics in Measurement 2017

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KV Discrete Time Signal Processing

Learning Outcome

This course aims to teach how to analyse and design digital signal processing systems as well as the implementation in signal processors, to provide knowledge about the sources of error and the theory concerning signals and systems.

Course Content

  • Linear systems and Laplace transform (repetition)
  • Analogue filters (design methods, realisation)
  • Sampling theorem (mathematical description)
  • Digital Filters (FIR-filter, IIR-filter)
  • Properties and design rules
  • Filter structures (direct structures, cascade structures, lattice structures)
  • Effects of word length when using fixed comma arithmetics
  • Discrete Fourier transform (DFT, FFT, implementation)
  • Spectral analysis
  • Chirp-z transform
  • Cepstrum analysis
  • Multi rate systems

Learning Methods and Activities

Examples presented by lecturer, home exercises, written final exam


Combined exam with a written part fort the practical part and an oral part for the theory part. The practical part consists of 2 numeric examples which are to be solved in written form and lasts about 45 min and is followed by an oral examination which covers the theory. In addition three home exercises have to be handed in which count about a third towards the grade of the practical part.


  • Lecture notes: Digitale Signalverarbeitung (KV)
  • Oppenheim, Alan V. ; Schafer, Roland W.: Discrete-Time Signal Processing - Third Edition. Pearson, 2010
  • Oppenheim, Alan V. ; Schafer, Roland W. ; Buck, John R.: Zeitdiskrete Signalverarbeitung – 2. überarbeitete Auflage. Prentice Hall, 2004