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December 2006 Efficient independent component analysis
Aiyou Chen, Peter J. Bickel
Ann. Statist. 34(6): 2825-2855 (December 2006). DOI: 10.1214/009053606000000939


Independent component analysis (ICA) has been widely used for blind source separation in many fields, such as brain imaging analysis, signal processing and telecommunication. Many statistical techniques based on M-estimates have been proposed for estimating the mixing matrix. Recently, several nonparametric methods have been developed, but in-depth analysis of asymptotic efficiency has not been available. We analyze ICA using semiparametric theories and propose a straightforward estimate based on the efficient score function by using B-spline approximations. The estimate is asymptotically efficient under moderate conditions and exhibits better performance than standard ICA methods in a variety of simulations.


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Aiyou Chen. Peter J. Bickel. "Efficient independent component analysis." Ann. Statist. 34 (6) 2825 - 2855, December 2006.


Published: December 2006
First available in Project Euclid: 23 May 2007

zbMATH: 1114.62033
MathSciNet: MR2329469
Digital Object Identifier: 10.1214/009053606000000939

Primary: 62G05
Secondary: 62H12

Keywords: asymptotically efficient , B-splines , efficient score function , generalized M-estimator , Independent component analysis , semiparametric models

Rights: Copyright © 2006 Institute of Mathematical Statistics


Vol.34 • No. 6 • December 2006
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