Correlation Matching Approach To Source Separation In The Presence Of Spatially Correlated Noise

This paper addresses a new method of source separation that is robust in the presence of spatially correlated but temporally white noise. The method exploits the non-vanishing temporal structure of sources to reduce the effect of noise. In the framework of correlation matching, we develop two efficient least squares algorithm. Useful behavior of the proposed algorithms is confirmed by numerical experiments