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Clustering of signals using incomplete independent component analysis

Keck, I. R. ; Lang, Elmar ; Nassabay, S. ; Puntonet, C. G.



Abstract

In this paper we propose a new algorithm for the clustering of signals using incomplete independent component analysis (ICA). In the first step we apply the ICA to the dataset without dimension reduction, in the second step we reduce the dimension of the data to find clusters of independent components that are similar in their entries in the mixture matrix found by the ICA. We ...

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