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Data decomposition using independent component analysis with prior constraints

Abstract:

In many data analysis problems, it is useful to consider the data as generated from a set of unknown (latent) generators or sources. The observations we make of a system are then taken to be related to these sources through some unknown function. Furthermore, the (unknown) number of underlying latent sources may be less than the number of observations. Recent developments in independent component analysis (ICA) have shown that, in the case where the unknown function linking sources to observa...

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Publication status:
Published

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Authors


Roberts, S More by this author
Choudrey, R More by this author
Journal:
PATTERN RECOGNITION
Volume:
36
Issue:
8
Pages:
1813-1825
Publication date:
2003-08-05
DOI:
ISSN:
0031-3203
URN:
uuid:88aa695f-105d-4374-bbb5-17b6ddf3fe52
Source identifiers:
318917
Local pid:
pubs:318917

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