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  Independent Component Analysis (2001) [663 citations — 57 self]

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by Patrik O. Hoyer, Mika Inki
Neural Computing Surveys
http://www.cis.hut.fi/~phoyer/papers/gz/TICA.ps.gz
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Abstract:

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 iindependentj components are often not at all independent. We propose that this residual dependence structure could be used to dene a topographic order for the components. In particular, a distance between two components could be dened 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

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