Blind signal separation: mathematical foundations of ICA, sparse component analysis, and other techniques

The present paper shows mathematical foundations of ICA (independent component analysis) and related subjects of signal representations. Information geometry plays a basic role for elucidating the structure of the problem underlying signal representation and decomposition. The method of estimating function is used for the analysis of errors and stability for various ICA algorithms. The nonholonomic method is of particularly interest.

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