Blind Identification and Separation of Noisy Source Signals : Neural Network Approaches

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

[2]  Shun-ichi Amari,et al.  Adaptive approach to blind source separation with cancellation of additive and convolutional noise , 1996, Proceedings of Third International Conference on Signal Processing (ICSP'96).

[3]  Christian Jutten,et al.  Blind source separation for convolutive mixtures , 1995, Signal Process..

[4]  Andrzej Cichocki,et al.  Robust learning algorithm for blind separation of signals , 1994 .

[5]  S. Amari,et al.  Fast-convergence filtered regressor algorithms for blind equalisation , 1996 .

[6]  Andrzej Cichocki,et al.  Neural network approach to blind separation and enhancement of images , 1996, 1996 8th European Signal Processing Conference (EUSIPCO 1996).

[7]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[8]  Jean-François Cardoso,et al.  Equivariant adaptive source separation , 1996, IEEE Trans. Signal Process..

[9]  Andrzej Cichocki,et al.  Stability Analysis of Learning Algorithms for Blind Source Separation , 1997, Neural Networks.

[10]  Andrzej Cichocki,et al.  Robust neural networks with on-line learning for blind identification and blind separation of sources , 1996 .

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

[12]  Erkki Oja,et al.  One-unit Learning Rules for Independent Component Analysis , 1996, NIPS.

[13]  Ehud Weinstein,et al.  Criteria for multichannel signal separation , 1994, IEEE Trans. Signal Process..

[14]  P. Comon,et al.  Contrasts for multichannel blind deconvolution , 1996, IEEE Signal Processing Letters.

[15]  Andrzej Cichocki,et al.  Neural networks for blind decorrelation of signals , 1997, IEEE Trans. Signal Process..