Blind separation of uniformly distributed signals: A general approach

IEEE Transactions on Neural Networks

Volumn 10, Issue 5, 1999, Pages 1173-1185

  Basak, Jayanta ^a,b   Amari, Shun Ichi ^a,c  

^a IEEE

^b INDIAN STATISTICAL INSTITUTE   (India)

^c RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; LEARNING ALGORITHMS; MAXIMUM LIKELIHOOD ESTIMATION; SIGNAL PROCESSING; SPURIOUS SIGNAL NOISE;

BLIND SEPARATION; UNIFORMLY DISTRIBUTED SIGNALS;

NEURAL NETWORKS;

EID: 0032594917     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.788656     Document Type: Article

References (24)

1. S. Amari, "Neural theory of association and concept formation," Biol. Cybern., vol. 26, pp. 175-185, 1977.
2. _, "Natural gradient works efficiently in learning," Neural Comput., vol. 10, pp. 251-276, 1998.
3. S. Amari, T. P. Chen, and A. Cichocki, "Stability analysis of adaptive blind source separation," Neural Networks, vol. 10, pp. 1345-1351, 1997.
4. S.-I. Amari and J. F. Cardoso, "Blind source separation - Semiparametric statistical approach," IEEE Trans. Signal Processing, vol. 45, pp. 2692-2700, 1997.
5. S.-I. Amari, A. Cichocki, and H. H. Yang, "Recurrent neural networks for blind separation of sources." in Proc. Int. Symp. Nonlinear Theory Applicat., 1995, pp. 37-42.
6. _, "A new learning algorithm for blind signal separation." in Neural Information Processing Systems: Natural and Synthetic, NIPS'96, D. S. Touretzky, M. C. Mozer, and E. Hasselmo, Eds. Cambridge, MA: MIT Press, 1996, pp. 757-763.
7. J. Basak and S. Amari, "Blind separation of a mixture of uniformly distributed signals," Neural Comput., vol. 11, pp. 1011-1034, 1999.
8. _, "Blind separation of uniformly distributed source signals," in Proc. Int. Symp. Nonlinear Theory Applicat., 1997, pp. 997-1000.
9. A. J. Bell and T. J. Sejnowski, "An information maximization approach to blind separation and blind deconvolution," Neural Comput., vol. 7, pp. 1129-1159, 1995.
10. J. F. Cardoso and B. Laheld, "Equivariant adaptive source separation," IEEE Trans. Signal Processing, vol. 44, pp. 3017-3030, 1996.
11. A. Cichocki, S.-I. Amari, M. Adachi, and W. Kasprzak, "Self-adaptive neural networks for blind separation of sources," in Proc. Int. Symp. Circuits Syst., Atlanta, GA, USA, 1996, pp. 157-161.
12. P. Comon, "Independent component analysis, a new concept?," Signal Processing, vol. 36, pp. 287-314, 1994.
13. A. Hyvarinen and E. Oja, "Independent component analysis by general nonlinear Hebbian-like learning rules," Signal Processing, vol. 64, pp. 301-313, 1998.
14. C. Jutten and J. Herault, "Blind separation of sources, part i: An adaptive algorithm based on neuromimetic architecture," Signal Processing, vol. 24, pp. 1-20, 1991.
15. J. Karhunen and J. Joutsensalo, "Representation and separation of signals using nonlinear pea type learning," Neural Networks, vol. 7, pp. 113-127, 1994.
16. _, "Genralizations of principal component analysis, optimization problems, and neural networks," Neural Networks, vol. 8, pp. 549-562, 1995.
17. S. Kullback," Information Theory and Statistics. New York: Wiley, 1959.
18. K. Matsuoka, M. Ohya, and M. Kawamoto, "A neural net for blind separation of nonstationary signals," Neural Networks, vol. 8, pp. 411-419, 1995.
19. E. Oja, "A simplified neuron model as a principal component analyzer," J. Math. Biol., vol. 15, pp. 267-273, 1982.
20. E. Oja and J. Karhunen, "Signal separation by nonlinear hebbian learning." in Computational Intelligence - A Dynamic Systems Perspective, M. Palaniswami, Y. Attikiouzel, R. MarksII, D. Fogel, and T. Fukuda, Eds. New York: IEEE Press, 1995, pp. 83-97.
21. E. Oja, J. Karhunen, L. Wang, and R. Vigario, "Principal and independent components in neural networks - Recent developments," in Proc. Italian Wkshp. Neural Networks, WIRN'95, Vietn, Italy.
22. A. Prieto, C. G. Puntonet, and B. Prieto, "A neural learning algorithm for blind separation of sources based on geometric properties," Signal Processing, vol. 64, pp. 315-331, 1998.
23. C. R. Rao," Linear Statistical Inference and Its Applications. New York: Wiley, 1973.
24. H. H. Yang and S. Amari, "Adaptive on-line learning algorithms for blind separation - Maximum entropy and minimum mutual information," Neural Comput., vol. 9, pp. 1457-1482, 1997.