Sprache der Veranstaltung:
  • Englisch
Termin Vorlesung:
  • Di 12:00h-16:00h
    LMS lab room 06.021 (Cauerstr. 7)
  • 2,5 ECTS
UnivIS Links:


13.11.2019: There are still some free places available for this lab. If you are interested, contact Alexander Schmidt (alexander.as.schmidt@fau.de).

1.9.2019: You can register for this course on StudOn. The registration will start at the beginning of October. Further information on this will follow soon.  


After a short introduction to Python, the following topics are covered:

  • Basic properties of random variables and stochastic processes

  • Properties of correlation matrices, Principal Component Analysis, KLT

  • Parametric and non-parametric linear signal models

  • MMSE-based signal estimation

  • Kalman Filtering with applications to acoustic source tracking

  • Optimal multichannel filtering approaches

  • Introduction to adaptive filtering

In the second part of the course, the students will work in small groups independently on projects covering a topic from current research.


The lab will start approximately at the beginning/mid of December. All participants will meet beforehand to discuss all details. For this, you will receive a separate mail.

Place & Time

The course will take place in the lab rooms of LMS, Cauerstr. 7, 91058 Erlangen (6th floor) on

  • Dec 3, 12:00h-16:00h,
  • Dec 17, 12:00h-16:00h,
  • Jan 7, 12:00h-16:00h,
  • Jan 14, 12:00h-16:00h,
  • Jan 21, 12:00h-16:00h