Blind separation of nonstationary and temporally correlated sources from noisy mixtures

We present a new method of blind source separation that is robust with respect to additive white noise. Our method exploits the nonstationarity and temporal structure of sources. The method needs only multiple time-delayed correlation matrices of the observation data at several different time-windowed frames to estimate the mixing matrix. We present an implementation based on the joint diagonalization. Extensive simulations verify the high performance of the proposed method, especially in a low SNR environment.

[1]  Antoine Souloumiac,et al.  Jacobi Angles for Simultaneous Diagonalization , 1996, SIAM J. Matrix Anal. Appl..

[2]  J. Cardoso,et al.  Blind beamforming for non-gaussian signals , 1993 .

[3]  Schuster,et al.  Separation of a mixture of independent signals using time delayed correlations. , 1994, Physical review letters.

[4]  Kiyotoshi Matsuoka,et al.  A neural net for blind separation of nonstationary signals , 1995, Neural Networks.

[5]  Christoph E. Schreiner,et al.  Blind source separation and deconvolution: the dynamic component analysis algorithm , 1998 .

[6]  Jean-Francois Cardoso,et al.  Source separation using higher order moments , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[7]  S. Amari,et al.  Flexible Independent Component Analysis , 1998, Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378).

[8]  Hagai Attias,et al.  Blind Source Separation and Deconvolution: The Dynamic Component Analysis Algorithm , 1998, Neural Computation.

[9]  Shun-ichi Amari,et al.  Estimating Functions of Independent Component Analysis for Temporally Correlated Signals , 2000, Neural Computation.

[10]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[11]  P. Philips,et al.  JADETD : COMBINING HIGHER-ORDER STATISTICS AND TEMPORALINFORMATION FOR BLIND SOURCE SEPARATION ( WITH NOISE ) , 1999 .

[12]  Eric Moulines,et al.  A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..

[13]  Lang Tong,et al.  Indeterminacy and identifiability of blind identification , 1991 .