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Independent Component Analysis by Wavelets

By Pascal Barbedor

Abstract

22 pagesInternational audienceWe propose an ICA contrast based on the density estimation of the observed signal and its marginals by means of wavelets. The risk of the associated moment estimator is linked with approximation properties in Besov spaces. It is shown to converge faster than the at least expected minimax rate carried over from the underlying density estimations. Numerical simulations performed on some common types of densities yield very competitive results, with a high sensitivity to small departures from independence

Topics: ICA, wavelets, Besov spaces, nonparametric density estimation, 62H12 62G05, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], [STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]
Publisher: HAL CCSD
Year: 2009
DOI identifier: 10.1007/s11749-007-0073-7
OAI identifier: oai:HAL:hal-00005736v2
Provided by: Hal-Diderot
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