ELCE801
Advanced Signal Processing and Analysis

Course Description

This course introduces classical and contemporary methods in signal processing and analysis with particular emphasis on problems in biomedical research. Main topics include: stochastic signals and systems: random processes, white noise, stationarity, correlations, properties of linear time-invariant systems excited by white noise, entropy and information measures; time-frequency analysis: Fourier transform and spectral analysis, wavelets transform and multi-resolution analysis; optimal and adaptive filters: matched filters, Wiener filters and Kalman filters; multivariate signal decomposition and analysis: principal component analysis and independent component analysis, blind source separation; examples from biomedical signal processing and image processing, simulation and implementation with MATLAB?.


Prerequisite

Probability and Statistics, Digital Signal Processing, MATLABĀ® Programming


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