Separability of convolutive mixtures based on Wiener filtering and mutual information criterion

In this paper, we focus on convolutive mixtures, expressed in the time-domain. We present a method based on the minimization of the mutual information and using wiener filtering. Separation is known to be obtained by testing the independence between delayed outputs. This criterion can be much simplified and we prove that testing the independence between the contributions of all sources on the same sensor at same time index also leads to separability. We recover the contribution by using Wiener filtering (or Minimal Distortion Principal) which is included in the separation procedure. The independence is tested here with the mutual information. It is minimized only for non-delayed outputs of the Wiener filters. The test is easier and shows good results on simulation.