Prof. Doering

This course is about the analysis, classification and modelling of noisy, non-deterministic signals, with a particular emphasis on biosignals. The methodological focus is put on linear and non-parametric models. The practical part (lab exercises) will be implemented in MATLAB. Prerequisites to this course comprise: Fourier Transform for time-discrete signals (DTFT), Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT), basic digital filter design (Fourier design). Video lectures are provided for some of these prerequisites. (Note: These videos are in German, though.)

Overview:

• acquisition, quantisation, discretisation of biosignals
• statistical signal parameters
• filter design methods, optimal filters, adaptive filters
• parametric and non-parametric spectral analysis
• Time – Frequency – Analysis (short term Fourier Analysis, Wigner-Ville Distribution, Cohen's class distributions)
• Methods of Blind Source Separation (Principal Component Analysis, Independent Component Analysis)
• classification of signals / signal sections