A quasi-optimally efficient algorithm for independent component analysis

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

Volumn 5, Issue , 2004, Pages

  Weng, John J ^a   Zhang, Nan ^a  

^a Michigan State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HEURISTIC MEASUREMENTS; INDEPENDENT COMPONENT ANALYSIS (ICA); NONLINEAR FUNCTIONS; RANDOM VECTORS;

ALGORITHMS; DATA REDUCTION; FUNCTIONS; MATHEMATICAL MODELS; MATRIX ALGEBRA; SIGNAL PROCESSING; STATISTICAL METHODS; VECTORS;

BLIND SOURCE SEPARATION;

EID: 4544260425     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

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3. B.A. Olshausen and D.J. Field, "Emergence of simple-cell receptive field properties by learning a sparse code for natural images," Nature, vol. 381, pp. 607-609, 1996.
4. J. Karvanen and A. Cichocki, "Measuring sparseness of noisy signals," in Proceedings of 4th International symposium on Independent Component Analysis and Blind Signal Seperation (ICA2003), 2003, pp. 125-130.
5. J. Weng, Y. Zhang, and W.-S. Hwang, "Candid covariance-free incremental principal component analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 8, pp. 1034-1040, 2003.
6. A. Hyvärinen, "Fast independent component analysis," in Independent Component Analysis: Principles and Practice, S. Roberts and R. Everson, Eds. Cambridge University Press, 2001, in press.
7. T.-W. Lee, M. Girolami, and T. J. Sejnowski, "Independent component analysis using an extended infomax algorithm for mixed sub-gaussian and super-gaussian sources," Neural Computation, vol. 11, no. 2, pp. 417-441, 1999.