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
Link To Document :
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