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.
You can find a schedule here. Check it regularly since there might be changes!
Computer labs at the Chair of Multimedia Communications and Signal Processing, Wetterkreuz 15, 91058 Erlangen.
You have to register for this course. For this, get member of the StudOn group.