Practical Course Biosignal Processing and Modeling
Lecturer (assistant) |
|
---|---|
Number | 0000002816 |
Type | |
Duration | 4 SWS |
Term | Sommersemester 2017 |
Language of instruction | English |
Position within curricula | See TUMonline |
Dates | See TUMonline |
Dates
- 24.04.2017 12:15-13:00 2026, Karlstraße-Seminarraum, Introduction Meeting
- 28.04.2017 11:30-13:00 2001, Bibliothek, Group 1
- 28.04.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 05.05.2017 11:30-13:00 2001, Bibliothek, Group 1
- 05.05.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 12.05.2017 11:30-13:00 2001, Bibliothek, Group 1
- 12.05.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 19.05.2017 11:30-13:00 2001, Bibliothek, Group 1
- 19.05.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 26.05.2017 11:30-13:00 2001, Bibliothek, Group 1
- 26.05.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 02.06.2017 11:30-13:00 2001, Bibliothek, Group 1
- 02.06.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 09.06.2017 11:30-13:00 2001, Bibliothek, Group 1
- 09.06.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 16.06.2017 11:30-13:00 2001, Bibliothek, Group 1
- 16.06.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 23.06.2017 11:30-13:00 2001, Bibliothek, Group 1
- 23.06.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 30.06.2017 11:30-13:00 2001, Bibliothek, Group 1
- 30.06.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 07.07.2017 11:30-13:00 2001, Bibliothek, Group 1
- 07.07.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 14.07.2017 11:30-13:00 2001, Bibliothek, Group 1
- 14.07.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 21.07.2017 11:30-13:00 2001, Bibliothek, Group 1
- 21.07.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
- 28.07.2017 11:30-13:00 2001, Bibliothek, Group 1
- 28.07.2017 13:15-14:45 2001, Bibliothek, MSNE Students only
Admission information
Description
Theoretical lectures and hands-on practical tutorials on state of the art sensor systems, methods in experiment design, offline and online signal processing and pattern recognition/Machine learning
Prerequisites
Programming skills in C/C++ are recommended, background in MATLAB, basic knowledge in statistical signal processing and machine learning
Examination
schriftlicher Bericht und mündlich