A novel adaptive learning rate sequential blind source separation algorithm
Jafari, MG, Chambers, JA and Mandic, DP (2004) A novel adaptive learning rate sequential blind source separation algorithm Signal Processing, 84 (4). pp. 801-804.
Full text not available from this repository.Abstract
A new member of the family of natural gradient algorithms for on-line blind separation of independent sources is proposed. The method is based upon an adaptive step-size which varies in sympathy with the dynamics of the input signals and properties of the de-mixing matrix, and is robust to the perturbations in the initial value of the learning rate parameter. As a result, the convergence speed is significantly improved, especially in non-stationary mixing environments. Simulations support the expected improvement in convergence speed of the approach. © 2003 Elsevier B.V. All rights reserved.
Item Type: | Article | ||||||||||||
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Authors : |
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Date : | 1 April 2004 | ||||||||||||
Identification Number : | 10.1016/j.sigpro.2003.12.012 | ||||||||||||
Depositing User : | Symplectic Elements | ||||||||||||
Date Deposited : | 17 May 2017 13:27 | ||||||||||||
Last Modified : | 17 May 2017 13:27 | ||||||||||||
URI: | http://epubs.surrey.ac.uk/id/eprint/839258 |
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