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• W2149569475 abstract "We couple the tasks of source separation and density estimation by extracting the local geometrical structure of distributions obtained from mixtures of statistically independent sources. Our modifications of the self-organizing map (SOM) algorithm results in purely digital learning rules which perform non-parametric histogram density estimation. The non-parametric nature of the separation allows for source separation of non-linear mixtures. An anisotropic coupling is introduced into our SOM with the role of aligning the network locally with the independent component contours. This approach provides an exact verification condition for source separation with no prior on the source distributions." @default.
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• W2149569475 date "1996-12-03" @default.
• W2149569475 modified "2023-09-26" @default.
• W2149569475 title "Source Separation and Density Estimation by Faithful Equivariant SOM" @default.
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