Blind source separation-semiparametric statistical approach

IEEE Transactions on Signal Processing

Volumn 45, Issue 11, 1997, Pages 2692-2700

  Amari, Shun Ichi ^a   Cardoso, Jean François ^a  

^a RIKEN   (Japan)

Author keywords

Blind source separation; Estimating function; Independent component analysis; Learning algorithm; Semiparametric statistical model

Indexed keywords

ESTIMATION; LEARNING ALGORITHMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; MATRIX ALGEBRA; NEURAL NETWORKS; STATISTICAL METHODS;

BLIND SOURCE SEPARATION; SEMIPARAMETRIC STATISTICAL MODELS;

SIGNAL FILTERING AND PREDICTION;

EID: 0031271273     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/78.650095     Document Type: Article

References (22)

1. S. Amari, Differential-Geometrical Method in Statistics. New York: Springer-Verlag, 1985, vol 28.
2. ___, "Natural gradient works efficiently in learning," Neural Comput., to be published.
3. ___, "Information geometry," in Geometry and Nature, H. Necka and J.-P. Bourguignon, Eds., Contemporary Math., vol. 203, pp. 81-95, 1997.
4. ___, "Superefficiency in blind source separation," submitted for publication.
5. S. Amari, T.-P. Chen, and A. Cichocki, "Stability analysis of adaptive blind source separation," Neural Networks, to be published.
6. S. Amari, A. Cichocki, and H. Yang, "A new learning algorithm for blind signal separation," in Advances in Neural Information Processing Systems, D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo, Eds. Cambridge, MA: MIT Press, 1996, pp. 757-763, vol. 8.
7. S. Amari, S. C. Douglas, A. Cichocki, and H. H. Yang, "Novel online adaptive learning algorithms for blind deconvolution using the natural gradient approach," in Proc. IFAC Symp. Syst. Identification, Kitakyushu-shi, 1997, pp. 1055-1062.
8. S. Amari and M. Kawanabe, "Estimating functions in semiparametric statistical models," in Estimating Functions, V. P. Godambe, Ed., 1997, IMS Monograph Series.
9. ___, "Information geometry of estimating functions in semiparametric statistical models," Bernoulli, vol. 3, pp. 29-54, 1997.
10. 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.
11. P. J. Bickel, C. A. J. Klaassen, Y. Ritov, and J. A. Wellner, Efficient and Adaptive Estimation for Semiparametric Models. Baltimore, MD: Johns Hopkins Univ. Press, 1993.
12. J.-F. Cardoso and B. Laheld, "Equivariant adaptive source separation," IEEE Trans. Signal Processing, vol. 44, pp. 3017-3030, Dec. 1996.
13. J.-F. Cardoso and A. Souloumiac, "Blind beamforming for non Gaussian signals," Proc. IEEE, vol. 140, pp. 362-370, Dec. 1993.
14. P. Common, "Independent component analysis, a new concept?," Signal Process., vol. 36, pp. 287-314, 1994.
15. A. Gorokhov and J.-F. Cardoso, "Equivariant blind deconvolution of MIMO-FIR channels," in Proc. Signal Process. Adv. Wireless Commun. Workshop, Paris, France, 1997, pp. 89-92.
16. C. Jutten and J. Hérault, "Independent component analysis versus PCA," in Proc. EUSIPCO, 1988, pp. 643-646.
17. J. Karhunen and J. Joutsensalo, "Representation and separation of signals using nonlinear PCA type learning," Neural Networks, vol. 7, no. 1, pp. 113-127, 1993.
18. B. G. Lindsay, "Using emprical partially Bayes inference for increased efficiency," A. Statist., vol. 13, pp. 914-931, 1985.
19. M. K. Murray and J. W. Rice, Differential Geometry and Statistics. New York: Chapman & Hall, 1993.
20. J.-P. Nadal and N. Parga, "Nonlinear neurons in the low-noise limit: A factorial code maximizes information transfer," Network, vol. 7, pp. 565-581, 1994.
21. D. T. Pham, "Blind separation of instantaneous mixtures of sources via an independent component analysis," IEEE Trans. Signal Processing, vol. 44, pp. 2768-2779, 1996.
22. D. T. Pham, P. Garrat, and C. Jutten, "Separation of a mixture of independent sources through a maximum likelihood approach," in Proc. EUSIPCO, 1992, pp. 771-774.