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
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;
Conference_Titel :
Neural Networks for Signal Processing, 2002. Proceedings of the 2002 12th IEEE Workshop on
Print_ISBN :
0-7803-7616-1
DOI :
10.1109/NNSP.2002.1030066