Practical Course Biosignal Processing and Modeling
| Lecturer (assistant) | |
|---|---|
| Number | 0000002816 |
| Type | |
| Duration | 4 SWS |
| Term | Sommersemester 2019 |
| Language of instruction | English |
| Position within curricula | See TUMonline |
| Dates | See TUMonline |
Dates
- 26.04.2019 11:30-14:00 2001, Bibliothek, Kick-off Meeting
- 26.04.2019 14:00-16:30 2001, Bibliothek, Kick-off Meeting
- 03.05.2019 11:30-14:00 2001, Bibliothek, Group1
- 03.05.2019 14:00-16:30 2001, Bibliothek, MSNE Students only
- 10.05.2019 11:30-14:00 2001, Bibliothek, Group1
- 10.05.2019 14:00-16:30 2001, Bibliothek, MSNE Students only
- 17.05.2019 11:30-14:00 2001, Bibliothek, Group1
- 17.05.2019 14:00-16:30 2001, Bibliothek, MSNE Students only
- 24.05.2019 11:30-14:45 2001, Bibliothek, Group1
- 24.05.2019 15:00-18:15 2001, Bibliothek, MSNE Students only
- 31.05.2019 11:30-14:45 2001, Bibliothek, Group1
- 31.05.2019 15:00-18:15 2001, Bibliothek, MSNE Students only
- 07.06.2019 11:30-14:45 2001, Bibliothek, Group1
- 07.06.2019 15:00-18:15 2001, Bibliothek, MSNE Students only
- 14.06.2019 11:30-14:45 2001, Bibliothek, Group1
- 14.06.2019 15:00-18:15 2001, Bibliothek, MSNE Students only
- 21.06.2019 11:30-14:45 2001, Bibliothek, Group1
- 21.06.2019 15:00-18:15 2001, Bibliothek, MSNE Students only
- 28.06.2019 11:30-14:00 2001, Bibliothek, Group1
- 28.06.2019 14:00-16:30 2001, Bibliothek, MSNE Students only
- 05.07.2019 11:30-14:00 2001, Bibliothek, Group1
- 05.07.2019 14:00-16:30 2001, Bibliothek, MSNE Students only
- 12.07.2019 11:30-14:00 2001, Bibliothek, Group1
- 12.07.2019 14:00-16:30 2001, Bibliothek, MSNE Students only
- 19.07.2019 11:30-14:00 2001, Bibliothek, Group1
- 19.07.2019 14:00-16:30 2001, Bibliothek, MSNE Students only
- 26.07.2019 11:30-14:00 2001, Bibliothek, Group1
- 26.07.2019 14:00-16:30 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