The contents of the lecture include:
Robust Signal Processing and Learning
- Measuring robustness
- Robust estimation of the mean and the variance
- Robust regression models
- Robust filtering
- Robust location and covariance estimation
- Robust clustering and classification
- Robust time-series and spectral analysis
Biomedical Applications
- Body-worn sensing of physiological parameters
- Electrocardiogram (ECG)
- Photoplethysmogram (PPG)
- Eye research
- Intracranial Pressure (ICP)
- Algorithms for cardiac activity monitoring
This course is maintained via . Please register via moodle to gain access to the moodle course. TUCaN
Course Overview
Lecture/Tutorial Time and Room |
Wednesdays, 1.30-3.10 p.m. (online) Thursdays, 1.30-3.10 p.m. (online) (first lecture on April 23, 2020) |
Office Hours | Michael Muma: contact me via email |
Prerequisites | Fundamental knowledge of statistical signal processing (Digital Signal Processing) |
Language | English |
Format | Lecture and Tutorial (L3+T1); 6 credit points |
Assessment | Written exam |
Literature
- Zoubir, A. M. and Koivunen, V. and Ollila, E. and Muma, M.: Robust Statistics for Signal Processing. Cambridge University Press, 2018.
- Zoubir, A. M. and Koivunen, V. and Chackchoukh J, and Muma, M. Robust Estimation in Signal Processing: A Tutorial-Style Treatment of Fundamental Concepts. IEEE Signal Proc. Mag. Vol. 29, No. 4, 2012, pp. 61-80.
Toolboxes
Matlab, Python and R Toolboxes that implement the algorithms that are treated in the lecture are available here:
https://github.com/RobustSP/