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Titel:

Information-theoretic model selection for independent components

Autor(en):
Plant, C.; Theis, F. J.; Meyer-Bäse, A.; Böhm, C.
Abstract:
Independent Component Analysis (ICA) is an essential building block for data analysis in many applications. Selecting the truly meaningful components from the result of an ICA algorithm, or comparing the results of different algorithms, however, are non-trivial problems. We introduce a very general technique for evaluating ICA results rooted in information-theoretic model selection. The basic idea is to exploit the natural link between non-Gaussianity and data compression: The better the data tr...     »
Herausgeber:
Vigneron, V.; Zarzoso, V.; Moreau, E.
Band / Teilband / Volume:
6365
Verlag / Institution:
Springer
Verlagsort:
Berlin
Jahr:
2010
Seiten:
254-262
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