Topographic Independent Component Analysis

Author:

Hyvärinen Aapo1,Hoyer Patrik O.1,Inki Mika1

Affiliation:

1. Neural Networks Research Centre, Helsinki University of Technology, FIN-02015 HUT, Finland

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 “independent” components are often not at all independent. We propose that this residual dependence structure could be used to define a topo-graphic 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.

Publisher

MIT Press - Journals

Subject

Cognitive Neuroscience,Arts and Humanities (miscellaneous)

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