Blind source separation based on power spectral density

Authors:
JingHui Wang;YuanChao Zhao
Affiliations:
Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, TianJin, China;Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, TianJin, China
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Year:
2011

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Abstract

In this paper, a novel blind separation approach using power spectral density(PSD) is presented. The power spectrum itself is the Fourier transform of the auto-correlation function. Auto-correlation function represents the relationship of long and short-term correlation within the signal itself. This paper using power spectral density and cross power spectral density separate blind mixed source signals. In practice, non-stationary signals always have different PSD. The method is suitable for dealing with non-stationary signal. And simulation results have shown that the method is feasible.