Chair of
Multimedia Communications and Signal Processing
Prof. Dr.-Ing. André Kaup

Statistical Signal Processing

Lecturer:Prof. Dr.-Ing. Walter Kellermann
Tutor:M.Sc. Alexander Schmidt
Type:Lecture
Lecture language:English
Time Lecture:Tue 12:15-13:45 H17 Maschinenbau*
Wed 14:15-15:45 H12*
Time Supplements:Thu 14:15-15:45 HF*
Credit Points:5 ECTS
Hours (Lecture):3
Hours (Exercise):1
Prerequisites:Signals and Systems I, Signals and Systems II, Probability theory or Stochastic Processes

All data marked with a * are directly imported from UnivIS


News

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

Content

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

Schedule

Here, you can find the schedule for winter term 2017/2018, where V and Ü denote lectures and supplements, respectively. As there may be changes, check the schedule regularly.

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)
0
4
5
6

Literature

  • 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)