DocumentCode
1656080
Title
Geometric algorithms for the non-whitened one-unit linear Independent Component Analysis problem
Author
Shen, Hao ; Diepold, Klaus ; Huper, Knut
Author_Institution
Inst. for Data Process., Tech. Univ. Munchen, Munich, Germany
fYear
2009
Firstpage
381
Lastpage
384
Abstract
In this paper, we study the problem of one-unit linear independent component analysis (ICA) without whitening. The FastICA algorithm is arguably the most popular algorithm for solving the whitened one-unit linear ICA problem. Although a modified FastICA has been already proposed to solve the non-whitened one-unit linear ICA problem, there is unfortunately no known analysis regarding its effectiveness and efficiency. In this work, the non-whitened FastICA algorithm is revisited and analyzed in the framework of geometric optimization algorithms. In this paper, a conjugate gradient (CG) algorithm for the non-whitened one-unit linear ICA problem is developed as well. Local convergence properties of both algorithms are discussed. Finally, local convergence performance of the algorithms is investigated by several numerical experiments.
Keywords
blind source separation; independent component analysis; optimisation; conjugate gradient algorithm; geometric optimization algorithms; nonwhitened one-unit linear independent component analysis problem; Algorithm design and analysis; Blind source separation; Character generation; Convergence of numerical methods; Data processing; Independent component analysis; Mathematics; Principal component analysis; Robustness; Source separation; Independent component analysis (ICA); conjugate gradient (CG) algorithm; fixed point algorithm; nonwhitening; unit sphere;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
Conference_Location
Cardiff
Print_ISBN
978-1-4244-2709-3
Electronic_ISBN
978-1-4244-2711-6
Type
conf
DOI
10.1109/SSP.2009.5278560
Filename
5278560
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