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Erschienen in:
2012 | OriginalPaper | Buchkapitel
To Infinity and Beyond: On ICA over Hilbert Spaces
verfasst von : Harold W. Gutch, Fabian J. Theis
Erschienen in: Latent Variable Analysis and Signal Separation
Verlag: Springer Berlin Heidelberg
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The original Independent Component Analysis (ICA) problem of blindly separating a mixture of a finite number of real-valued statistically independent one-dimensional sources has been extended in a number of ways in recent years. These include dropping the assumption that all sources are one-dimensional and some extensions to the case where the sources are not real-valued. We introduce an extension in a further direction, no longer assuming only a finite number of sources, but instead allowing infinitely many. We define a notion of independent sources for this case and show separability of ICA in this framework.