DocumentCode
2200050
Title
Simple algorithms for decorrelation-based blind source separation
Author
Douglas, Scott C.
Author_Institution
Dept. of Electr. Eng., Southern Methodist Univ., Dallas, TX, USA
fYear
2002
fDate
2002
Firstpage
545
Lastpage
554
Abstract
We present simple adaptive algorithms that perform blind source separation for spatially-independent and temporally-correlated source signals. The proposed algorithms are modified versions of a well-known natural gradient prewhitening scheme, and the simplest version has almost the same complexity as this prewhitening method. We provide a stationary point analysis of our schemes, proving that the only locally-stable stationary point results in separated sources with unit variances and a guaranteed output ordering. We also show how to modify the approaches so that joint subspace analysis and decorrelation-based source separation are performed. Simulations verify the separation capabilities of the schemes.
Keywords
adaptive signal processing; blind source separation; computational complexity; decorrelation; gradient methods; statistical analysis; adaptive algorithms; blind source separation; decorrelation; joint subspace analysis; natural gradient prewhitening scheme; spatially-independent source signals; stationary point analysis; temporally-correlated source signals; Adaptive algorithm; Algorithm design and analysis; Analysis of variance; Blind source separation; Decorrelation; Gradient methods; Iterative algorithms; Performance analysis; Source separation; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Signal Processing, 2002. Proceedings of the 2002 12th IEEE Workshop on
Print_ISBN
0-7803-7616-1
Type
conf
DOI
10.1109/NNSP.2002.1030066
Filename
1030066
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