A novel adaptive learning rate sequential blind source separation algorithm

Authors:
M. G. Jafari;J. A. Chambers;D. P. Mandic
Affiliations:
Centre for Digital Signal Processing Research, King's College London, London, UK;Cardiff School of Engineering, Cardiff University, Cardiff, UK;Communications and Signal Processing Research Group, Imperial College, London, UK
Venue:
Signal Processing
Year:
2004

Citing 2
Cited 1

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A stochastic gradient adaptive filter with gradient adaptive stepsize

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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.