Sprache der Veranstaltung:
  • Englisch
Termin Vorlesung:
  • Mo 16:15-17:45 H5
    Di 14:15-15:45 H10
  • 5 ECTS
Stunden Vorlesung:
  • 3
UnivIS Links:


No news at the moment.


Will be announced at the beginning of the semester.


The course concentrates on fundamental methods of statistical signal processing and their applications. The main topics are:

  • Discrete-time stochastic processes in the time and frequency domain
  • Estimation theory
  • Non-parametric and parametric signal models (pole/zero models, ARMA models)
  • Optimum linear filters (e.g. for prediction), eigenfilters, Kalman filters
  • Algorithms for optimum linear filter identification (adaptive filters)

Course material

To keep up to date, please register for the course on StudOn (password in first lecture).

Extra points for the written exam

Extra points for the written exam can be obtained by handing in the homework. Please note:
1.) The homework is to be prepared in groups of two.
2.) Copying from another group will result in zero points.
3.) All calculations for arriving at an answer must be shown.
4.) If you fail in the exam without extra points, they cannot be taken into account.
5.) The extra points expire for the resit.

Number of passed worksheets:
0 - 3.5
4 - 4.5
5 - 5.5
6 - 6.5
Extra points for the written exam:
(based on 100 achievable points)


  • A. Papoulis, S. Pillai: Probability, Random Variables and Stochastic Processes; McGraw-Hill, 2002 (english)
  • D. Manolakis, V. Ingle, S. Kogon: Statistical and Adaptive Signal Processing; Artech House, 2005 (english)

Voraussetzungen / Organisatorisches

Signale und Systeme I, Signale und Systeme II, Wahrscheinlichkeitsrechnung oder Stochastische Prozesse