A practical formulation for computation of complex gradients and its application to maximum likelihood ICA

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 2, Issue , 2007, Pages

  Adah, Tülay ^a   Li, Hualiang ^a  

^a UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

Author keywords

Maximum likelihood estimation; Optimization methods; Signal analysis

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; INDEPENDENT COMPONENT ANALYSIS; MAXIMUM LIKELIHOOD ESTIMATION; OPTIMIZATION;

COMPLEX-VALUED SIGNAL PROCESSING; OPTIMIZATION METHODS;

SIGNAL ANALYSIS;

EID: 34547500747     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2007.366315     Document Type: Conference Paper

References (21)

1. T. Adali, T. Kim, and V. D. Calhoun, "Independent component analysis by complex nonlinearities," in Proc. ICASSP, Montreal, Canada, 2004.
2. S.-I. Amari, "Natural gradient works efficiently in learning," Neural Computation, vol, 10, pp, 251-276, 1998.
3. P. O. Amblard, M. Gaeta, J. L. Lacoume, "Statistics for complex variables and signals-Part 1: Variables," Signal Proc. vol. 53, pp. 1-13, 1996.
4. J. Anemüller, T. J. Sejnowski, and S. Makeig, "Complex independent component analysis of frequency-domain electroencephalographic data," Neural Networks, vol. 16, pp. 1311-1323, 2003.
5. E. Bingham and A. Hyvarinen, "A fast fixed-point algorithm for independent component analysis of complex-valued ssignals," Int. J. Neural Syst., vol. 10, pp. 1-8, 2000.
6. D. Brandwood, "A complex gradient operator and its application in adaptive array theory "Proc. IEE., vol. 130, pp. 11-16, Feb. 1983.
7. S. De Simoni, "Su una estensione dello schema delle curve normali di ordine r alle variabili doppie," Statistica, vol, 37, pp. 447-474, 1968.
8. A. J. Bell and T. J, Sejnowski, "An information maximisation approach to blind separation and blind deconvolution," Neural Comput., vol. 7, pp. 1129-1159, 1995.
9. J.-F. Cardoso and T. Adali, "The maximum likelihood approach to complex ICA," in Proc. ICASSP 2006, Toulouse, France, 2006.
10. J.-F. Cardoso and B. Laheld, "Equivariant adaptive source separation," IEEE Trans. Signal Proc. vol. 44, pp. 3017-3030, Dec. 1996.
11. J.-F. Cardoso and A. Souloumiac, "Blind beamforming for nongaussian signals," IEE Proc. Radar Signal Proc., vol. 140, pp. 362-370, 1993.
12. A. Cichocki and R. Unbehauen, "Robust neural networks with online learning for blind identification and blind separation of sources" IEEE Trans. Circuits Syst. I: Fund. Theory Apps., vol, 43, pp, 894-906, 1996.
13. J. Eriksson and V. Koivunen, "Complex-valued ICA using second order statistics," in Proc. MLSP, Saõ Luis, Brazil, 2004.
14. J. Eriksson, A. Seppola and V. Koivunen, "Complex ICA for circular and non-circular sources," in Proc. EUSIPCO, Antalya, Turkey, 2005.
15. A. Hyvarinen, "Fast and robust fixed-point algorithms for independent component analysis," IEEE Trans. Neural Networls, vol. 10, pp. 626-634, 1999.
16. T. Kim and T. Adali, "Approximation by fully complex Multilayer Perceptrons" Neural Comput., vol. 15, pp. 1641-1666, 2003.
17. M. Novey and T. Adah, "Adaptable nonlinearity for complex maximization of nongaussianity and a fixed-point algorithm," in Proc. IEEE Workshop on Machine Learning for Signal Processing (MLSP), Maynooth, Ireland, Sep. 2006.
18. H. Li and T. Adali, "Gradient and fixed-point complex ICA algorithms based on kurtosis maximization," in Proc. IEEE Workshop on Machine Learning for Signal Processing (MLSP), Maynooth, Ireland, Sep, 2006.
19. D.-T. Pham and P. Garat, "Blind Separation of Mixture of Independent Sources Through a Quasi-Maximum Likelihood Approach," IEEE Trans. Signal Processing, vol, 45, pp, 1712-1725, July 1997.
20. P. Smaragdis, "Blind Separation of Convolved Mixtures in the Frequency Domain" Neurocomputing, vol. 22, pp. 21-34, 1998.
21. A. van den Bos, "Complex gradient and hessian," IEE Proc. Vision, Image. and Signal Processing, vol. 141, no. 6, pp, 380-383, December 1994.