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Gradient Algorithm for Nonnegative Independent Component Analysis.
- Source :
- Advances in Neural Networks - ISNN 2006; 2006, p1115-1120, 6p
- Publication Year :
- 2006
-
Abstract
- A novel algorithm is proposed for the nonnegative independent component analysis. In the algorithm, we employ the gradient algorithm with some modifications to separate nonnegative independent sources from mixtures. Since the local convergence of the gradient algorithm is already proved, the result in this paper will be considered one of the convergent nonnegative ICA algorithms. Simulation shows the proposed algorithm can separate the mixtures of nonnegative signals very successfully. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISBNs :
- 9783540344391
- Database :
- Supplemental Index
- Journal :
- Advances in Neural Networks - ISNN 2006
- Publication Type :
- Book
- Accession number :
- 32883779
- Full Text :
- https://doi.org/10.1007/11759966_164