SOURCE SEPARATION OF TEMPORALLY CORRELATED SOURCE USING BANK OF BAND PASS FILTERS

This paper introduces a new source separation algorithms exploiting the difference in the spectra shapes of the source signals. The proposed approach relies only on second-order statistics and estimates the mixing matrix by using eigenvalue decomposition of covariance matrix of prewithened sensor signals or alternatively an input output identification procedure using as inputs linear band pass filtered versions of the estimated colored sources. An adaptive implementation of the proposed technique is presented. The new algorithm shows to be computationally very simple and efficient. In addition and in contrast to other existing techniques, the covariance of the noise do not need to be modeled. The effectiveness of the proposed method is illustrated by some numerical simulations.