A novel measure for independent component analysis (ICA)

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 2, Issue , 1998, Pages 1161-1164

  Xu, Dongxin ^a   Principe, Jose C ^a   Fisher, John ^a   Wu, Hsiao Chun ^a  

^a University of Florida   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENGINEERING APPLICATIONS; INDEPENDENCE MEASURE; INDEPENDENT COMPONENT ANALYSIS(ICA); INFORMATION ENTROPY; NONPARAMETRIC ESTIMATORS; PARZEN WINDOWS; RENYI'S ENTROPY; THEORETICAL FOUNDATIONS;

BLIND SOURCE SEPARATION; INDEPENDENT COMPONENT ANALYSIS; POTENTIAL ENERGY; PROBABILITY DENSITY FUNCTION;

SIGNAL PROCESSING;

EID: 84892189639     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.1998.675476     Document Type: Conference Paper

References (14)

1. Hartley, R.V. "Transmission of information". Bell System Technical Journal, 7, 1928.
2. Shannon, C.E. "A mathematical theory of communication". Bell Sys. Tech. J. 27, 1948, pp379-423
3. Renyi, A. "Some Fundamental Questions of Information Theory". Selected Papers of Alfred Renyi, Vol 2.
4. Renyi, A. "On Measures of Entropy and Information". Selected Papers of Alfred Renyi, Vol. 2. pp 565-580
5. Kapur, J.N. "Measures of Information and Their Applications". John Wiley &Sons. 1994
6. Jumarie, G "Relative Information, theory and applications", Springer-Verlag. 1990
7. Parzen, E. "On the estimation of a probability density function and the mode", Ann. Math. Stat. 33, 1962, pi065
8. Fisher, J. III. "Non-linear extensions to the minimum average correlation energy filter" Ph.D dissertation, Dept. of Electrical Engineering, University of Florida. 1997.
9. Bell, A.J. and Sejnowski, T.J. "An information-maximization approach to blind separation and blind deconvolution", Neural Comput., Vol.7, no.6, ppl004-1034
10. Yang, H.H. and Amari S. "Adaptive on-line learning algorithms for blind separation -maximum entropy and minimum mutual information", to appear in Neural Computation, 1997
11. Cardoso, J.-F. "Infomax and Maximum Likelihood for Blind Source Separation", IEEE Signal Processing Letters, Vol. 4. No. 4. April 1997, ppll2-114
12. Rumelhart, D.E., Hinton. G.E. and Williams. J.R. "Learning representations by back-propagating errors", Nature (London), 323, 1986, pp533-536.
13. Vapnik, V.N. "The Nature of Statistical Learning Theory", Springer, 1995.
14. Linskcr R. "An application of the principle of maximum information preservation to linear systems", in Advances in Neural Information Processing Systems 1, Touretzky D.S. (ed). Morgan-Kauffman