A normalised kurtosis-based algorithm for blind source extraction from noisy measurements

Authors:
Wei Liu;Danilo P. Mandic
Affiliations:
Communications Research Group, Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, UK;Communications and Signal Processing Research Group, Department of Electrical and Electronic Engineering, Imperial College London, UK
Venue:
Signal Processing
Year:
2006

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Abstract

In blind extraction of independent sources, the normalised Kurtosis is a normally used cost function for the cases without the initial prewhitening. The applications of this method are, however, limited to noise-free mixtures, which is not realistic. We therefore address this issue and propose a new cost function based on the normalised Kurtosis, which makes this class of algorithms suitable for noisy environments, a typical situation in practice. The proposed method is justified by a theoretical analysis and the performance of the derived algorithm is demonstrated by simulations.