Xu L. (2007). One-bit-matching theorem for ICA, convex-concave programming on polyhedral set, and distribution approximation for combinatorics. Neural computation. 19 [PubMed]

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References and models cited by this paper

Amari SI, Chen TP. (1997). Stability analysis of adaptive blind source separation Neural Networks Letter. 10

Amari SL, Cichocki A, Yang HH. (1996). A new learning algorithm for blind signal separation. Advances in Neural Information Processing Systems.. 8

Bazaraa MS, Sherali HD, Shetty CM. (1993). Nonlinear programming theory and algorithms (2nd ed).

Bell AJ, Sejnowski TJ. (1995). An information-maximization approach to blind separation and blind deconvolution. Neural computation. 7 [PubMed]

Cardoso JF. (1998). Blind source separation: Statistical principles Proc IEEE. 86

Comon P. (1994). Independent component analysis, a new concept? Signal Processing. 36

Delfosse N, Loubaton P. (1995). Adaptive blind separation of independent sources: A deflation approach Signal Processing. 45

Edelman A, Arias TA, Smith ST. (1998). The geometry of algorithms with orthogonality constraints SIAM J Matrix Anal Appl. 20

Everson R, Roberts S. (1999). Independent component analysis: A flexible nonlinearity and decorrelating manifold approach. Neural computation. 11 [PubMed]

Girolami M. (1998). An alternative perspective on adaptive independent component analysis algorithms Neural computation. 10 [PubMed]

Hopfield JJ, Tank DW. (1985). "Neural" computation of decisions in optimization problems. Biological cybernetics. 52 [PubMed]

Lee TW, Girolami M, Sejnowski TJ. (1999). Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources. Neural computation. 11 [PubMed]

Liu R, Tong L, Inouye Y. (1993). Waveform-preserving blind estimation of multiple independent sources Signal Processing. 41

Liu ZY, Chiu KC, Xu L. (2004). One-bit-matching conjecture for independent component analysis. Neural computation. 16 [PubMed]

Moreau E, Macchi O. (1996). High-order contrasts for self-adaptive source separation International Journal Of Adaptive Control And Signal Processi. 10

Oja E, Hyvarinen A, Karunen J. (2001). Independent component analysis.

Parra LC, Pearlmutter BA. (1996). A context-sensitive generalization of ICA International Conference on Neural Information Processing.

Welling M, Weber M. (2001). A constrained EM algorithm for independent component analysis. Neural computation. 13 [PubMed]

Xu L. (1994). Combinatorial optimization neural nets based on a hybrid of Lagrange and transformation approaches Proc World Congress on Neural Networks.

Xu L. (1995). On the hybrid LT combinatorial optimization: New U-shape barrier, sigmoid activation, least leaking energy and maximum entropy Proc Intl Conf Neural Inform Process.

Xu L. (1997). Bayesian ying-yang learning based ICA models Proc. 1997 IEEE Signal Processing Society Workshop on Neural Networks for Signal Processing VII.

Xu L. (2003). Distribution approximation, combinatorial optimization, and Lagrange-barrier Proc Intl Joint Conf Neural Networks.

Xu L. (2005). One-bit-matching ICA theorem, convex-Concave programming, and Combinatorial optimization Advances in neural information processing systems.

Xu L, Amari SI, Cheung CC. (1998). Further results on nonlinearity and separtion capability of a liner mixture ICA method and learned lpm Proceedings of the IANN98.

Xu L, Amari SI, Cheung CC. (1998). Learned parametric mixture based ICA algorithm Neurocomputing. 22

Xu L, Amari SI, Yang H, Cheung C. (1997). Independent component analysis by the information-theoretic approach with mixture of densities Proc. of 1997 IEEE Intl. Conf on Neural Networks (IEEE-INNS IJCNN97).

Xu L, Cheung CC. (2000). Some global and local convergence analysis on the information-theoretic independent component analysis approach Neurocomputing. 30

Xu L, Yang HH, Amari SI. (1996). Signal source separation by mixtures: accumulative distribution functions or mixture of bell-shape density distribution functions Research proposal presented at FRONTIER FORUM.

References and models that cite this paper
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