Discrete-time signal processing

Brief description

The lecture Discrete Time Signal Processing provides an introduction to elementary techniques of digital signal processing. Particular emphasis is placed on a description that is as clear and practice-orientated as possible. Students gain their own practical experience in the exercises through the use of Python.

Lecture contents

  • Discrete-time signals: elementary signals, even/odd signals, harmonic exponential oscillations
  • Fourier series of periodic discrete-time signals: Parseval theorem, symmetry relations
  • Discrete-time systems: LTI, impulse response
  • Fourier transform of discrete-time signals
  • Sampling theorem
  • Difference equations and z-transform
  • FIR and IIR filter design
  • DFT, FFT
  • Cyclic convolution, overlap-add and overlap-save
  • Multirate signal processing

Learning outcomes & professional competences

After completing this course, students will be able to

  • describe discrete-time signals and systems in the time and frequency domain using signal processing methods
  • analyse and evaluate discrete-time systems with regard to stability, transient response, etc.
  • design self-contained digital filters with specified properties
  • realise digital filters in software in a computationally efficient manner
  • implement more complex signal processing algorithms in Python in a computationally efficient manner

The students

  • have acquired extensive skills in Python, which can also be used outside the realisation of signal processing algorithms,
  • can design, implement and test a programme from a given task and evaluate, present and discuss the results obtained,
  • can analyse more extensive tasks together in a group, break them down into subtasks and work on them in a solution-oriented manner.

Methodical realisation

  • Lectures with predominantly blackboard use, occasional slide presentations
  • Classroom exercises with exercise sheets and demonstrations on the computer
  • Practical exercises with Python, in which students independently develop solutions and implement, test and analyse signal processing algorithms.

Recommended literature

Doblinger, Gerhard: "Zeitdiskrete Signale und Systeme", An introduction to the basic methods of digital signal processing


  • Course for Bachelor students
  • ECTS: 6
  • Language: German
  • Semester: Summer term


business-card image

Dr.-Ing. Jörg Schmalenströer

Communications Engineering / Heinz Nixdorf Institute

(Contract)-Research & Teaching

Write email +49 5251 60-3623


business-card image

Tobias Gburrek

Communications Engineering / Heinz Nixdorf Institute

Research & Teaching

Write email +49 5251 60-3624