High-order contrasts for independent component analysis

Neural Computation

Volumn 11, Issue 1, 1999, Pages 157-192

  Cardoso, Jean François ^a  

^a TELECOM PARISTECH   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; STATISTICAL MODEL;

ALGORITHMS; MODELS, NEUROLOGICAL; MODELS, STATISTICAL;

EID: 0032612381     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976699300016863     Document Type: Article

References (28)

1. Amari, S.-I. (1996). Neural learning in structured parameter spaces - Natural Riemannian gradient. In Proc. NIPS.
2. Amari, S.-I., Cichocki, A., & Yang, H. (1996). A new learning algorithm for blind signal separation. In Advances in neural information processing systems, 8 (pp. 757-763). Cambridge, MA: MIT Press.
3. Bell, A. J., & Sejnowski, T. J. (1995). An information-maximisation approach to blind separation and blind deconvolution. Neural Computation, 7, 1004-1034.
4. Cardoso, J.-F. (1992). Fourth-order cumulant structure forcing. Application to blind array processing. In Proc. 6th SSAP workshop on statistical signal and array processing (pp. 136-139).
5. Cardoso, J.-F. (1994). On the performance of orthogonal source separation algorithms. In Proc. EUSIPCO (pp. 776-779). Edinburgh.
6. Cardoso, J.-F. (1995). The equivariant approach to source separation. In Proc. NOLTA (pp. 55-60).
7. Cardoso, J.-F. (1997). Infomax and maximum likelihood for source separation. IEEE Letters on Signal Processing, 4, 112-114.
8. Cardoso, J.-F. (1998). Blind signal separation: statistical principles. Proc. of the IEEE. Special issue on blind identification and estimation.
9. Cardoso, J.-F., Bose, S., & Friedlander, B. (1996). On optimal source separation based on second and fourth order cumulants. In Proc. IEEE Workshop on SSAP. Corfu, Greece.
10. Cardoso, J.-F., & Laheld, B. (1996). Equivariant adaptive source separation. IEEE Trans. on Sig. Proc., 44, 3017-3030.
11. Cardoso, J.-F., & Souloumiac, A. (1993). Blind beamforming for non Gaussian signals. IEEE Proceedings-F, 140, 362-370.
12. Comon, P. (1994). Independent component analysis, a new concept? Signal Processing, 36, 287-314.
13. Comon, P. (1997). Cumulant tensors. In Proc. IEEE SP Workshop on HOS. Banff, Canada.
14. Cover, T. M., & Thomas, J. A. (1991). Elements of information theory. New York: Wiley.
15. De Lathauwer, L., De Moor, B., & Vandewalle, J. (1996). Independent component analysis based on higher-order statistics only. In Proc. IEEE SSAP Workshop (pp. 356-359).
16. Gaeta, M., & Lacoume, J. L. (1990). Source separation without a priori knowledge: The maximum likelihood solution. In Proc. EUSIPCO (pp. 621-624).
17. Golub, G. H., & Van Loan, C. F. (1989). Matrix computations. Baltimore: Johns Hopkins University Press.
18. MacKay, D. J. C. (1996). Maximum likelihood and covariant algorithms for independent component analysis. In preparation. Unpublished manuscript.
19. Makeig, S., Bell, A., Jung, T.-P., & Sejnowski, T. J. (1997). Blind separation of auditory event-related brain responses into independent components. Proc. Nat. Acad. Sci. USA, 94, 10979-10984.
20. McCullagh, P. (1987). Tensor methods in statistics. London: Chapman and Hall.
21. Moreau, E., & Macchi, O. (1996). High order contrasts for self-adaptive source separation. International Journal of Adaptive Control and Signal Processing, 10, 19-46.
22. Moulines, E., Cardoso, J.-F., & Gassiat, E. (1997). Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models. In Proc. ICASSP'97 (pp. 3617-3620).
23. Nadal, J.-P., & Parga, N. (1994). Nonlinear neurons in the low-noise limit: A factorial code maximizes information transfer. NETWORK, 5, 565-581.
24. Obradovic, D., & Deco, G. (1997). Unsupervised learning for blind source separation: An information-theoretic approach. In Proc. ICASSP (pp. 127-130).
25. Pearlmutter, B. A., & Parra, L. C. (1996). A context-sensitive generalization of ICA. In International Conference on Neural Information Processing (Hong Kong).
26. Pham, D.-T. (1996). Blind separation of instantaneous mixture of sources via an independent component analysis. IEEE Trans. on Sig. Proc., 44, 2768-2779.
27. Pham, D.-T., & Garat, P. (1997). Blind separation of mixture of independent sources through a quasi-maximum likelihood approach. IEEE Tr. SP, 45, 1712-1725.
28. Souloumiac, A., & Cardoso, J.-F. (1991). Comparaison de méthodes de séparation de sources. In Proc. GRETSI. Juan les Pins, France (pp. 661-664).