Decomposition algorithms for analysing brain signals
K. Robert Müller, Jens Kohlmorgen, Andreas Ziehe, Benjamin Blankertz · 2002
Analyzing biomedical data-e.g. from the brain-we encounter fundamental problems that lie largely in the fields of signal processing and machine learning. The current paper presents at first a method to deal with non-stationary signals, subsequently the signal processing technique of independent component analysis (ICA) is reviewed. We use EEG recordings of continuous auditory perception as illustration for the discussed algorithms.