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ICA
2007
Springer

A Robust Complex FastICA Algorithm Using the Huber M-Estimator Cost Function

14 years 4 months ago
A Robust Complex FastICA Algorithm Using the Huber M-Estimator Cost Function
In this paper, we propose to use the Huber M-estimator cost function as a contrast function within the complex FastICA algorithm of Bingham and Hyvarinen for the blind separation of mixtures of independent, non-Gaussian, and proper complex-valued signals. Sufficient and necessary conditions for the local stability of the complex-circular FastICA algorithm for an arbitrary cost are provided. A local stability analysis shows that the algorithm based on the Huber M-estimator cost has behavior that is largely independent of the cost function’s threshold parameter for mixtures of non-Gaussian signals. Simulations demonstrate the ability of the proposed algorithm to separate mixtures of various complex-valued sources with performance that meets or exceeds that obtained by the FastICA algorithm using kurtosis-based and other contrast functions.
Jih-Cheng Chao, Scott C. Douglas
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where ICA
Authors Jih-Cheng Chao, Scott C. Douglas
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