Lecture Language:
  • English
Hours (Lecture):
  • Mo 13:30-17:30
Time Lecture:
  • 3
UnivIS Links:

After an introduction to scientific programming with Python, experiments and exercises related to the following topics are carried out during the laboratory course:

  • Fundamental properties of random variables and stochastic processes

  • Properties of correlations matrices, Principal Component Analyis, KLT

  • Parametric and non-parametric linear signal models

  • MMSE signal estimation

  • Kalman filtering with applications to source tracking

  • Optimum multichannel filtering

  • Introduction to adaptive filtering.

In the second phase of the lab course, the students will work in small project teams on relevant research problems.


A first introductory meeting is scheduled for December, 12 (1:30pm-5:30pm). The first lab course will be on December, 19 (1:30pm-5:30pm).  

Lab facilities

Computer labs at the Chair of Multimedia Communications and Signal Processing, Wetterkreuz 15, 91058 Erlangen.