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Nonlinear Geometric ICA

Theis, Fabian J. ; Puntonet, Carlos G. ; Lang, Elmar Amari, S. , eds.



Abstract

We present a new algorithm for nonlinear blind source separation, which is based on the geometry of the mixture space. This space is decomposed in a set of concentric rings, in which we perform ordinary linear ICA after central transformation; we show that this transformation can be left out if we use linear geometric ICA. In any case, we get a set of images of ring points under the original ...

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