Finite sample effects of the fast ICA algorithm

Neurocomputing

Volumn 71, Issue 1-3, 2007, Pages 392-399

  Bermejo, Sergio ^a  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

Blind source separation; FastICA; High order statistics contrast functions; Independent component analysis; Sequential signal extraction

Indexed keywords

ALGORITHMS; BLIND SOURCE SEPARATION; ERROR ANALYSIS; PROBABILITY DISTRIBUTIONS; STATISTICS;

GENERALIZATION ERROR; HIGHER-ORDER STATISTICS (HOS); SAMPLE-FOURTH CUMULANT;

INDEPENDENT COMPONENT ANALYSIS;

ALGORITHM; ANALYTICAL ERROR; ARTICLE; INDEPENDENT COMPONENT ANALYSIS; PRIORITY JOURNAL; PROBABILITY; STANDARD; STATISTICAL ANALYSIS; STATISTICAL DISTRIBUTION;

EID: 35648989915     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2006.09.015     Document Type: Article

References (28)

1. Bermejo S. Finite sample effects in higher order statistics contrast functions for sequential blind source separation. IEEE Signal Proc. Lett. 12 6 (2005) 481-484
2. Bermejo S., Jutten C., and Cabestany J. ISFET source separation: foundations and techniques. Sensors Actuators B: Chem. 113 (2006) 222-233
3. Bishop C.M. Neural Networks for Pattern Recognition (1995), Oxford University Press, Oxford
4. Briselli E., et al. An independent component analysis-based approach on ballistocardiogram artifact removing. Magn. Resonance Imag. 24 4 (2006) 393-400
5. J.-F. Cardoso, Iterative techniques for blind source separation using only fourth order cumulants, in: Proceeding EUSIPCO, 1992, pp. 739-742.
6. J.-F. Cardoso, On the performance of orthogonal source separation algorithms, in: M. Holt, et al. (Eds.), Procceedings. EUSIPCO, VII European Signal Proceeding Conference, Edinburgh, Scotland, UK, September 1994, pp. 776-779.
7. Cardoso J.-F. Blind signal separation: statistical principles. Proc. IEEE 86 (1998) 2009-2025
8. Cardoso J.-F. Dependence, correlation and Gaussianity in independent component analysis. J. Machine Learn. Res. 4 (2003) 1177-1203
9. Cardoso J.-F., and Laheld B. Equivariant adaptive source separation. IEEE Trans. Signal Process. 44 12 (1996) 3017-3030
10. Cichocki A., and Amari S. Adaptive Blind Signal and Image Processing (2002), Wiley, New York
11. Delfosse N., and Loubaton P. Adaptive blind separation of independent sources: a deflation approach. Signal Process. 45 (1995) 59-83
12. S. Douglas, On the convergence behavior of the FastICA algorithm. in: Proceedings of the fourth International Symposium on Independent Component Analysis and Blind Signal Separation (ICA2003), April 2003, Japan.
13. Fan K., Wang M., Mo W., and Zhao X. Novel copyright protection scheme for digital content. J. Syst. Eng. Electron. 17 2 (2006) 423-429
14. H. Gävert, J. Hurri, J. Särelä, A. Hyvärinen, FastICA for Matlab 5.x, version 2.1, January 15, 2001.
15. Hyvärinen A., and Oja E. A fast fixed-point algorithm for independent component analysis. Neural Comput. 9 (1997) 1483-1492
16. Hyvärinen A., and Oja E. One-unit learning rules for independent component analysis. In: Mozer M., Jordan M., and Petsche T. (Eds). Advances in Neural Information Processing Systems (NIPS'1996) vol. 9 (1997), MIT Press, Cambridge, MA
17. Hyvärinen A., Karhunen K., and Oja E. Independent Component Analysis (2001), Wiley, New York
18. Longbottom J., Walden A.T., and White R.E. Principles and applications of maximum kurtosis phase estimation. Geophys. Prospect. 36 (1988) 115-138
19. E. Oja, Convergence of the symmetrical FastICA algorithm. in: Proceedings of the Ninth International Conference on Neural Information Processing (ICONIP'02), vol. 3, pp. 1368-1372.
20. Shalvi O., and Weinstein E. New criteria for blind deconvolution of nonminimum phase systems (channels). IEEE Trans. Inform. Theor. 36 2 (1990) 312-321
21. Shang L., Huang D.S., Du J.-X., and Zheng C.-H. Palmprint recognition using FastICA algorithm and radial basis probabilistic neural network. Neurocomputing 69 13-15 (2006) 1782-1786
22. A. Stuart, K. Ord, Kendall's advanced theory of statistics, Distribution Theory, sixth ed., vol. I. Arnold, London, 1994.
23. Tugnait J.K. Comments on new criteria for blind deconvolution of nonminimum phase systems (channels). IEEE Trans. Inform. Theor. 38 1 (1992) 210-212
24. Vapnik V.N. Estimation of Dependences Based on Empirical Data (1982), Springer, Berlin
25. Vapnik V.N. Statistical Learning Theory (1998), Wiley, New York
26. Vapnik V.N. The Nature of Statistical Learning Theory. second ed (2000), Springer, Berlin
27. Yadava R.D.S., and Chaudhary R. Solvation, transduction and independent component analysis for pattern recognition in SAW electronic nose. Sensors Actuators B: Chem. 113 1 (2006) 1-21
28. Yeredor A. Non-orthogonal joint diagonalization in the least-squares sense with application in blind source separation. IEEE Trans. Signal Process. 50 7 (2002) 1545-1553