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Geometric Overcomplete ICA

Theis, Fabian J. ; Lang, Elmar


In independent component analysis (ICA), given some signal input the goal is to find an independent decomposition. We present an algorithm based on geometric considerations to decompose a linear mixture of more sources than sensor signals. We present an efficient method for the matrix-recovery step in the framework of a two-step approach to the source separation problem. The second step - sourcerecovery - uses the standard maximum-likelihood approach.

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