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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

Abstract

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. https://doi.org/10.1214/009053606000000939

Information

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

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

Subjects:
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

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Vol.34 • No. 6 • December 2006
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