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Proceedings Paper

Blind signal separation: mathematical foundations of ICA, sparse component analysis, and other techniques
Author(s): Shun-ichi Amari
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Paper Abstract

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.

Paper Details

Date Published: 28 March 2005
PDF: 10 pages
Proc. SPIE 5818, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks III, (28 March 2005); doi: 10.1117/12.607004
Show Author Affiliations
Shun-ichi Amari, RIKEN, Brain Science Institute (Japan)


Published in SPIE Proceedings Vol. 5818:
Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks III
Harold H. Szu, Editor(s)

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