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Independent Component Analysis

Aapo Hyvärinen, Patrik O. Hoyer, Mika Inki

The MIT Press eBooks · 2004 · 7,973 citations

Abstract

Neural Computation 13(7):1527-1558 [July, 2001] In ordinary independent component analysis, the components are assumed to be completely independent, and they do not necessarily have any meaningful order relationships. In practice, however, the estimated “independent” components are often not at all independent. We propose that this residual dependence structure could be used to define a topographic order for the components. In particular, a distance between two components could be defined using their higher-order correlations, and this distance could be used to create a topographic representation. Thus we obtain a linear decomposition into approximately independent components, where the dependence of two components is approximated by the proximity of the components in the topographic representation. 1

Cite this paper

Hyvärinen, A., Hoyer, P. O., & Inki, M. (2004). Independent component analysis. In The MIT Press eBooks (pp. 79–110). The MIT Press. https://doi.org/10.7551/mitpress/3717.003.0014

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