DocumentCode
1171238
Title
Consistent independent component analysis and prewhitening
Author
Chen, Aiyou ; Bickel, Peter J.
Author_Institution
Bell Labs., Lucent Technol., Murray Hill, NJ, USA
Volume
53
Issue
10
fYear
2005
Firstpage
3625
Lastpage
3632
Abstract
We study the statistical merits of two techniques used in the literature of independent component analysis (ICA). First, we analyze the characteristic-function based ICA method (CHFICA) and study its statistical properties such as consistency, √n-consistency, and robustness against small additive noise. Second, we study the validity of prewhitening: a preprocessing technique used by many ICA algorithms, as applied to the CHFICA method. In particular, we establish the surprising effectiveness of this technique even when some components have heavy tails and others do not. A fast new algorithm implementing the prewhitened CHFICA method is also provided.
Keywords
independent component analysis; signal processing; ICA; additive noise; asymptotic normality; characteristic-function based method; consistency; incomplete Cholesky decomposition; independent component analysis; preprocessing technique; prewhitening; signal processing; statistical properties; Additive noise; Blind source separation; Independent component analysis; Machine learning algorithms; Noise robustness; Parametric statistics; Signal analysis; Signal processing algorithms; Source separation; Tail; Asymptotic normality; characteristic function; consistency; incomplete Cholesky decomposition; independent component analysis; prewhitening;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2005.855098
Filename
1510972
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