### An Information-Maximization Approach to Blind Separation and Blind Deconvolution

暂无分享，去创建一个

[1] S. Laughlin. A Simple Coding Procedure Enhances a Neuron's Information Capacity , 1981, Zeitschrift fur Naturforschung. Section C, Biosciences.

[2] John G. Proakis,et al. Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[3] Christian Jutten,et al. Space or time adaptive signal processing by neural network models , 1987 .

[4] Ralph Linsker,et al. An Application of the Principle of Maximum Information Preservation to Linear Systems , 1988, NIPS.

[5] Eric A. Vittoz,et al. CMOS Integration of Herault-Jutten Cells for Separation of Sources , 1989, Analog VLSI Implementation of Neural Systems.

[6] Peter Földiák,et al. Adaptation and decorrelation in the cortex , 1989 .

[7] W. Bialek,et al. Optimal Sampling of Natural Images: A Design Principle for the Visual System , 1990, NIPS 1990.

[8] Simon Haykin,et al. Adaptive filter theory (2nd ed.) , 1991 .

[9] Terrence J. Sejnowski,et al. Competitive Anti-Hebbian Learning of Invariants , 1991, NIPS.

[10] Christian Jutten,et al. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Processing.

[11] J J Hopfield,et al. Olfactory computation and object perception. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[12] John C. Platt,et al. Networks for the Separation of Sources that Are Superimposed and Delayed , 1991, NIPS.

[13] Pierre Comon,et al. Blind separation of sources, part II: Problems statement , 1991, Signal Process..

[14] Thomas M. Cover,et al. Elements of Information Theory , 1991 .

[15] Esfandiar Sorouchyari,et al. Blind separation of sources, part III: Stability analysis , 1991, Signal Process..

[16] Ralph Linsker,et al. Local Synaptic Learning Rules Suffice to Maximize Mutual Information in a Linear Network , 1992, Neural Computation.

[17] Geoffrey E. Hinton,et al. Self-organizing neural network that discovers surfaces in random-dot stereograms , 1992, Nature.

[18] Schuster. Learning by maximizing the information transfer through nonlinear noisy neurons and "noise breakdown" , 1992, Physical review. A, Atomic, molecular, and optical physics.

[19] Schuster Hg. Learning by maximizing the information transfer through nonlinear noisy neurons and "noise breakdown , 1992 .

[20] Andreas G. Andreou,et al. Current-mode subthreshold MOS implementation of the Herault-Jutten autoadaptive network , 1992 .

[21] J. Urgen Schmidhuber. Learning Factorial Codes by Predictability Minimization , 1992 .

[22] Simon Haykin,et al. Blind equalization formulated as a self-organized learning process , 1992, [1992] Conference Record of the Twenty-Sixth Asilomar Conference on Signals, Systems & Computers.

[23] Jürgen Schmidhuber,et al. Learning Factorial Codes by Predictability Minimization , 1992, Neural Computation.

[24] Roberto Battiti,et al. First- and Second-Order Methods for Learning: Between Steepest Descent and Newton's Method , 1992, Neural Computation.

[25] Gilles Burel,et al. Blind separation of sources: A nonlinear neural algorithm , 1992, Neural Networks.

[26] Joseph J. Atick,et al. Convergent Algorithm for Sensory Receptive Field Development , 1993, Neural Computation.

[27] S. Hyakin,et al. Neural Networks: A Comprehensive Foundation , 1994 .

[28] J. Nadal. Non linear neurons in the low noise limit : a factorial code maximizes information transferJean , 1994 .

[29] Juha Karhunen,et al. Representation and separation of signals using nonlinear PCA type learning , 1994, Neural Networks.

[30] J. Nadal,et al. Nonlinear neurons in the low-noise limit: a factorial code maximizes information transfer Network 5 , 1994 .

[31] Schuster,et al. Separation of a mixture of independent signals using time delayed correlations. , 1994, Physical review letters.

[32] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Processing.

[33] Terrence J. Sejnowski,et al. A Non-linear Information Maximisation Algorithm that Performs Blind Separation , 1994, NIPS.

[34] Ehud Weinstein,et al. Criteria for multichannel signal separation , 1994, IEEE Trans. Signal Process..

[35] David J. Field,et al. What Is the Goal of Sensory Coding? , 1994, Neural Computation.

[36] Andreas G. Andreou,et al. Analog CMOS integration and experimentation with an autoadaptive independent component analyzer , 1995 .

[37] Terrence J. Sejnowski,et al. Adaptive separation of mixed broadband sound sources with delays by a beamforming Herault-Jutten network , 1995 .

[38] Y. Baram,et al. Multi-Dimensional Density Shaping by Sigmoidal Networks , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[39] Gustavo Deco,et al. Nonlinear higher-order statistical decorrelation by volume-conserving neural architectures , 1995, Neural Networks.

[40] L. Parra,et al. Redundancy reduction with information-preserving nonlinear maps , 1995 .

[41] Steve Rogers,et al. Adaptive Filter Theory , 1996 .

[42] Lucas C. Parra,et al. Statistical Independence and Novelty Detection with Information Preserving Nonlinear Maps , 1996, Neural Computation.