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IJON
2006

Sparse ICA via cluster-wise PCA

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Sparse ICA via cluster-wise PCA
In this paper, it is shown that Independent Component Analysis (ICA) of sparse signals (sparse ICA) can be seen as a cluster-wise Principal Component Analysis (PCA). Consequently, Sparse ICA may be done by a combination of a clustering algorithm and PCA. For the clustering part, we use, in this paper, an algorithm inspired from K-means. The final algorithm is easy to implement for any number of sources. Experiment results points out the good performance of the method, whose the main restriction is to request an exponential growing of the sample number as the number of sources increases.
Massoud Babaie-Zadeh, Christian Jutten, Ali Mansou
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where IJON
Authors Massoud Babaie-Zadeh, Christian Jutten, Ali Mansour
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