Elimination of filtering indeterminacy in blind source separation

Author:

Matsuoka Kiyotoshi

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference10 articles.

1. S. Amari, S.C. Douglas, A. Cichocki, H.H. Yang, Multichannel blind deconvolution and equalization using the natural gradient, in: Proceedings of the IEEE International Workshop on Wireless Communication, 1997, pp. 101–104.

2. S. Choi, S. Amari, A. Cichocki, R. Liu, Natural gradient learning with a nonholonomic constraint for blind deconvolution of multiple channels, in: Proceedings of the International Workshop on Independent Component Analysis and Blind Signal Separation (ICA’99), 1999, pp. 371–376.

3. M. Joho, Convolutive blind signal separation in acoustics by joint approximate diagonalization of spatiotemporal correlation matrices, in: Proceedings of the 38th Asilomar Conference on Signals, Systems, and Computers, 2004.

4. Blind separation of sources. Part I: An adaptive algorithm based on neuromimetic architecture;Jutten;Signal Process.,1991

5. K. Matsuoka, Principle for eliminating two kinds of indeterminacy in blind source separation, in: Proceedings of the DSP2002, 2002, pp. 147–150.

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