Blind source separation of real world signals

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 4, Issue , 1997, Pages 2129-2134

  Lee, Te Won ^a,b   Bell, Anthony J ^b   Orglmeister, Reinhold ^c  

^a MAX PLANCK INSTITUTE   (Germany)

^b SALK INSTITUTE FOR BIOLOGICAL STUDIES   (United States)

^c TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC SPEECH RECOGNITION SYSTEM; FREQUENCY DOMAINS; INFORMATION MAXIMIZATION; INVERSE SYSTEM; NON-CAUSAL FILTERS; POLYNOMIAL ALGEBRA; REAL ENVIRONMENTS; SPEECH SIGNALS;

ALGEBRA; NEURAL NETWORKS; DIGITAL FILTERS; POLYNOMIALS;

BLIND SOURCE SEPARATION; SPEECH RECOGNITION;

BLIND SOURCE SEPARATION; REAL WORLD SIGNALS;

EID: 0030658281     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.614235     Document Type: Conference Paper

References (19)

1. S. Amari, A. Cichocki, and H. Yang. A New Learning Algorithm for Blind Signal Separation. In Advances in Neural Information Processing System 8, 1996.
2. A. Bell and T. Sejnowski. An Information Maximization Approach to Blind Separation and Blind Deconvolution. Neural Computation, 7: 1129-1 159, July 1995.
3. J-F. Cardoso and B. Laheld. Equivariant adaptive source separation. IEEE Trans. on Signal Processing, 45,2:434-444, Dec. 1996.
4. J-E Cardoso. Infomax and maximum likelihood for blind source separation. to appear in IEEE Signal Processing Letters.
5. A. Cichocki, R. Unbehauen, and E. Rummert. Robust learning algorithm for blind separation of signals. Electronics Letters, 30, 17, 1386-1387, 1994
6. A. Cichocki, S. Amari and J. Cao. Blind separation of delayed and convolved signals with self-adaptive learning rate. In Proc. NOLTA'96, 1996.
7. P. Comon. Independent component analysis- A new concept? Signal Processing, 36(3):287-314,1994.
8. E. Ferrara. Fast implementation of lms adaptive filters, IEEE Transactions on Acoustics, Speech and Signal Processing, 28(4):474478,1980.
9. M. Girolami and C. Fyfe. Negentropy and kurtosis as projection pursuit indices provide generalised ica algorithms. In Advances in Neural Information Processing Systems Workshop 9, 1996.
10. J. Karhunen, E. Oja, L. Wang, R. Vigario, and J. Joutsensalo. A class of neural networks for independent component analysis. Report A28, Helsinki Univ. of Technology, October 1995. submitted to a journal.
11. R. Lambert, Multichannel blind deconvolution: Fir matrix algebra and separation of multipath mixtures, Thesis, University of Southern California, May, 1996, Department of Electrical Engineering
12. R. Lambert and A. Bell. Blind separation of multiple speakers in a multipath environment. in Proc. ICASSP 1997, Munich.
13. T. Lee, A. Bell and R. Lambert Blind separation of convolved and delayed sources. In Advances in Neural Information Processing Systems 9. MIT Press, 1997.
14. T. Lee and R. Orglmeister. A contextual blind separation of delayed and convolved sources. In Proc. ICASSP 1997, Munich.
15. D. T. Pham. Blind separation of instantaneous mixture of sources via an indpendent component analysis. IEEE Trans. on Signal Proc., 44, 11:2768-2779,1996.
16. B. Pearlmutter and L. Parra. A context-sensitive generalization of ICA. In ICONIP'96. In press.
17. Z. Roth and Y. Baram. Multidimensional density shaping by sigmoids. IEEE Trans. on Neural Networks, 7(5):1291-1298,1996.
18. Kari Torkkola. Blind separation of convolved sources based on information maximization. In IEEE Workshop on Neural Networks for Signal Processing, Kyoto, Japan, September 4-6 1996. (in press).
19. D. Yellin and E. Weinstein. Multichannel signal separation: Methods and analysis. IEEE Transactions on SignaE Processing, 44( 1): 106-1 18, January 1996.