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A blind source separation technique using second-order statistics

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4 Author(s)
Belouchrani, A. ; Dept. of Electr. & Comput. Eng., Villanova Univ., PA, USA ; Abed-Meraim, K. ; Cardoso, J.-F. ; Moulines, E.

Separation of sources consists of recovering a set of signals of which only instantaneous linear mixtures are observed. In many situations, no a priori information on the mixing matrix is available: The linear mixture should be “blindly” processed. This typically occurs in narrowband array processing applications when the array manifold is unknown or distorted. This paper introduces a new source separation technique exploiting the time coherence of the source signals. In contrast with other previously reported techniques, the proposed approach relies only on stationary second-order statistics that are based on a joint diagonalization of a set of covariance matrices. Asymptotic performance analysis of this method is carried out; some numerical simulations are provided to illustrate the effectiveness of the proposed method

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Signal Processing, IEEE Transactions on  (Volume:45 ,  Issue: 2 )