A unified method for blind separation of sparse sources with unknown source number

IEEE Signal Processing Letters

Volumn 13, Issue 1, 2006, Pages 49-51

  Lv, Qi ^a   Zhang, Xian Da ^a  

^a TSINGHUA NATIONAL LABORATORY FOR INFORMATION SCIENCE AND TECHNOLOGY   (China)

Author keywords

Blind source separation (BSS); Clustering; Sparse signal; Unsupervised robust C prototypes (URCP)

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; ESTIMATION; MATRIX ALGEBRA; SENSORS;

CLUSTERING; SPARSE SIGNAL; UNKNOWN SOURCE NUMBER; UNSUPERVISED ROBUST C PROTOTYPES;

BLIND SOURCE SEPARATION;

EID: 30444432202     PISSN: 10709908     EISSN: None     Source Type: Journal    
DOI: 10.1109/LSP.2005.860540     Document Type: Article

References (19)

1. H. Frigui and R. Krishnapuram, "A robust algorithm for automatic extraction of an unknown number of clusters from noisy data," Pattern Recognit. Lett., vol. 17, pp. 1223-1232, 1996.
2. C. Jutten and J. Herault, "Blind separation of sources part I: An adaptive algorithm based on neuromimetic architecture," Signal Process., vol. 24, pp. 1-10, 1991.
3. P. Comon, "Independent component analysis, a new concept?," Signal Process., vol. 36, pp. 287-314, 1994.
4. J. F. Cardoso and B. Laheld, "Equivariant adaptive source separation," IEEE Trans. Signal Process., vol. 44, no. 12, pp. 3017-3030, Dec. 1996.
5. 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.
6. J. Karhunen and J. Joutsensalo, "Representation and separation of signals using nonlinear PCA type learning," Neural Netw., vol. 7, pp. 113-127, 1994.
7. Q. Lv, X. D. Zhang, and Y. Jia, "Kalman filtering algorithm for blind source separation," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, vol. 5, Mar. 2005, pp. 257-260.
8. A. Cichocki, J. Karhunen, W. Kasprzak, and R. Vigario, "Neural networks for blind separation with unknown number of sources," Neurocomput., vol. 24, no. 1, pp. 55-93, 1999.
9. J. Wang and Z. He, "Multichannel blind identification with unknown number of sources," in Proc. IEEE TENCON Digital Signal Processing Applications, vol. 2, 1996, pp. 670-675.
10. L. Albera, A. Ferreol, P. Comon, and P. Chevalier, "Blind identification of overcomplete mixtures of sources (BIOME)," Linear Algebra Appl., vol. 391, pp. 3-30, 2004.
11. I. F. Gorodnitsky and B. D. Rao, "Sparse signal reconstruction from limited data using FOCUSS: Area-weighted minimum norm algorithm," IEEE Trans. Signal Process., vol. 45, no. 3, pp. 600-616, Mar. 1997.
12. M. S. Lewicki and T. J. Sejnowski, "Learning overcomplete representations," Neural Computat., vol. 12, pp. 337-365, 2000.
13. A. Belouchrani and J. F. Cardoso, "Maximum likelihood source separation for discrete sources," in Proc. EUSIPCO, 1994, pp. 768-771.
14. S. Araki, S. Makino, A. Blin, and H. Sawada, "Underdetermined blind separation for speech in real environments with sparseness and ICA," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, vol. 3, May 2004, pp. 881-884.
15. M. Zibulevsky, B. A. Pearlmutter, P. Bofill, and P. Kisilev, "Blind source separation by sparse decomposition," in Independent Component Analysis: Principles and Practice, S. J. Roberts and R. M. Everson, Eds. Cambridge, U.K.: Cambridge Univ. Press, 2001.
16. S. Haykin, Adaptive Filter Theory, 3rd ed. Englewood Cliffs, NJ: Prentice-Hall, 1996.
17. 1 norm solutions for underdetermined source separation," IEEE Trans. Signal Process., vol. 52, no. 3, pp. 582-591, Mar. 2004.
18. P. Bofill and M. Zibulevsky, "Blind separation of more sources than mixtures using sparsity of their short-time Fourier transform," in Proc. Int. Workshop Independent Component Analysis Blind Signal Separation, 2000, pp. 87-92.
19. P. Bofill, "Underdetermined blind separation of delayed sound sources in the frequency domain," Neurocomputing, vol. 55, pp. 627-641, 2003.