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Blind-Source Separation Based on Decorrelation and Nonstationarity

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3 Author(s)
Fuliang Yin ; Sch. of Electron. & Inf. Eng., Dalian Univ. of Technol. ; Tiemin Mei ; Jun Wang

In this paper, discrete-time blind-source separation (BSS) of instantaneous mixtures is studied. Decorrelation-based sufficient criteria for BSS of stationary and nonstationary sources are derived based on nonstationarity and nonwhiteness. A gradient algorithm is proposed based on these criteria. A batch-data algorithm and an on-line algorithm are developed based on the corollaries of the BSS criteria. These algorithms are especially useful for the separation of nonstationary sources. They are robust to additive white noises if the time-delayed decorrelation and the nonstationarity of the sources are considered simultaneously in the algorithms. Experiment results show the effectiveness and performance of the proposed algorithms

Published in:

IEEE Transactions on Circuits and Systems I: Regular Papers  (Volume:54 ,  Issue: 5 )