Separation of two independent sources by the information-theoretic approach with cubic nonlinearity

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 4, Issue , 1997, Pages 2239-2244

  Cheung, Chi Chiu ^a   Xu, Lei ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

CUBIC NONLINEARITIES; GRADIENT ALGORITHM; ICA ALGORITHMS; INDEPENDENT COMPONENT ANALYSIS(ICA); INDEPENDENT SOURCES; INFORMATION-THEORETIC APPROACH; MATHEMATICAL ANALYSIS; PARAMETER SPACES;

INDEPENDENT COMPONENT ANALYSIS; INFORMATION THEORY; NEURAL NETWORKS; ADAPTIVE CONTROL SYSTEMS; ALGORITHMS; CONTROL NONLINEARITIES; NUMERICAL ANALYSIS; PROBLEM SOLVING;

SOURCE SEPARATION; INFORMATION ANALYSIS;

GENERAL GRADIENT ALGORITHM; INDEPENDENT COMPONENT ANALYSIS (ICA);

EID: 0030707022     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.614377     Document Type: Conference Paper

References (8)

1. S.-I. Amari, A. Cichocki, H. Yang, A new learning algorithm for blind separation of sources, in David S. Touretzky, Michael C. Mozer & d Michael E. Has-selmo, eds, Advances in Neural Information Processing 8 (MIT Press: Cambridge, MA. 1996) 757-763.
2. A. J. Bell and T. J. Sejnowski, An information-maximatization approach to blind separation and blind deconvolution, Neural Computation 7 (1995) 1129-1159.
3. A. J. Bell and T. J. Sejnowski, Fast blind separation based on information theory, in Proc. 1996 Intl. Symp. on Nonlinear Theory and Its Applications (NOLTA 95) (Las Vegas, USA, Dec 10-14, 1995) 287-314.
4. J. Karhunen, Neural approaches to independent component analysis and source separation, invited paper, Proc. 4th European Symposium on Artificial Neural Networks (ESANN'96) (Bruges, Belgium April 24-26, 1996).
5. L. Xu, YING-YANG Machine: a Bayesian-Kullback scheme for unified learnings and new results on vector quantization, Keynote talk, in Proc. Intl Conf. on Neural Information Processing (ICONIP 95) (Beijing, China, Oct 30-Nov 3, 1995) 977-988.
6. L. Xu, A unified learning scheme: Bayesian-Kullback YING-YANG Machine, in David S. Touretzky, Michael C. Mozer & d Michael E. Hasselmo, eds, Advances in Neural Information Processing 8 (MIT Press: Cambridge, MA. 1996) 444-450.
7. L. Xu, Bayesian-Kullback YING-YANG Machine: reviews and new results, in Progress in Neural Information Processing: Proc. Intl. Conf. on Neural Information Processing (ICONIP 96) (Hong Kong, Sept 24-27, 1996; Springer-Verlag: Singapore 1996) 59-67.
8. L. Xu and S.-I. Amari, A general independent component analysis framework based on Bayesian-Kullback Ying-Yang Learning, in Progress in Neural Information Processing: Proc. Intl. Conf. on Neural Information Processing (ICONIP 96) (Hong Kong, Sept 24-27, 1996; Springer-Verlag: Singapore 1996) 1235-1239.