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ICA
2007
Springer

Blind Separation of Instantaneous Mixtures of Dependent Sources

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Blind Separation of Instantaneous Mixtures of Dependent Sources
Abstract. This paper deals with the problem of Blind Source Separation. Contrary to the vast majority of works, we do not assume the statistical independence between the sources and explicitly consider that they are dependent. We introduce three particular models of dependent sources and show that their cumulants have interesting properties. Based on these properties, we investigate the behaviour of classical Blind Source Separation algorithms when applied to these sources: depending on the source vector, the separation may be sucessful or some additionnal indeterminacies can be identified.
Marc Castella, Pierre Comon
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where ICA
Authors Marc Castella, Pierre Comon
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