Unsupervised learning for source separation with mixture of Gaussians prior for sources and Gaussian prior for mixture coefficients

Neural Networks for Signal Processing - Proceedings of the IEEE Workshop

Volumn , Issue , 2001, Pages 293-302

  Snoussi, Hichem ^a   Mohammad Djafari, Ali ^a  

^a CNRS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; PROBABILITY; SPURIOUS SIGNAL NOISE; VECTORS;

UNSUPERVISED LEARNING;

LEARNING SYSTEMS;

EID: 0035783805     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. A. Belouchrani, Séparation autodidacte de sources: Algorithmes, Performances et Application à des signaux expérimentaux, Phd thesis, Ecole Nationale Supérieure des Télécommunications, 1995.
2. A. Belouchrani and J.-F. Cardoso, "Maximum likelihood source separation for discrete sources," in EUSIPCO'94, 1994.
3. O. Bermond, Méthodes statistiques pour la séparation de sources, Phd thesis, Ecole Nationale Supérieure des Télécommunications, 2000.
4. J.W. Brewer, "Kronecker products and matrix calculus in system theory," IEEE Trans. Circ. Syst., vol. CS-25, no. 9, pp. 772 781, 1978.
5. J. Cardoso and B. Labeld, "Equivariant adaptative source separation," Signal Processing, vol. 44, pp. 3017-3030, 1996.
6. A.P. Dempster, N.M. Laird and D.B. Rubin, "Maximum Likelihood from incomplete data via the EM algorithm," J.R. Statist. Soc. B, vol. 39, pp. 1-38, 1977.
7. A.O. Hero and J.A. Fessler, "Asymptotic Convergence Properties of Em-Type Algorithms," Preprints 85-T-21, Dept. of Electrical Engineering and Computer Science, University of Michigan, 1985.
8. O. Macchi and E. Moreau, "Adaptative unsupervised separation of discrete sources," in Signal Processing, 1999, vol. 73, pp. 49-66.
9. E. Moreau and O. Macchi, "High-order contrasts for self-adaptative source separation," in Adaptative Control Signal Process. 10, 1996, pp. 19-46.
10. E. Moulines, J. Cardoso and E. Gassiat, "Maximum likelihood For Blind Separation And Deconvolution Of Noisy Signals Using Mixture Models," in ICassp-97, Munich, Germany, April 1997.
11. D. Ormoneit and V. Tresp, "Averaging, Maximum Penalized Likelihood and Bayesian Estimation for Improving Gaussian Mixture Probability Density Estimates," IEEE Transactions on Neural Networks, vol. 9, no. 4, pp. 639-649, July 1998.
12. R.A. Redner and H.F. Walker, "Mixture densities, maximum likelihood and the EM algorithm," SIAM Rev., vol. 26, no. 2, pp. 195-239, April 1984.
13. e coil GRETSI, Vannes, France, September 1999, pp. 259-262.
14. H. Snoussi and A. Mohammad-Djafari, "Dégénérescences des estimateurs MV en séparation de sources," Technical report ri-s0010, gpi-12s.
15. H. Snoussi and A. Mohammad-Djafari, "Bayesian source separation with mixture of Gaussians prior for sources and Gaussian prior for mixture coefficients," in A. Mohammad-Djafari (ed.), Bayesian Inference and Maximum Entropy Methods, MaxEnt Workshops, Gif-sur-Yvette, France: to appear in Amer. Inst. Physics, July 2000.