Nonlinear neurons in the low-noise limit: a factorial code maximizes information transfer Network 5
暂无分享,去创建一个
[1] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.
[2] Claude E. Shannon,et al. The Mathematical Theory of Communication , 1950 .
[3] F. Attneave. Some informational aspects of visual perception. , 1954, Psychological review.
[4] S. Laughlin. A Simple Coding Procedure Enhances a Neuron's Information Capacity , 1981, Zeitschrift fur Naturforschung. Section C, Biosciences.
[5] D J Field,et al. Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[6] Richard E. Blahut,et al. Principles and practice of information theory , 1987 .
[7] Ralph Linsker,et al. Self-organization in a perceptual network , 1988, Computer.
[8] Zee,et al. Understanding the efficiency of human perception. , 1988, Physical review letters.
[9] H. B. Barlow,et al. Finding Minimum Entropy Codes , 1989, Neural Computation.
[10] Peter Földiák,et al. Adaptation and decorrelation in the cortex , 1989 .
[11] William Bialek,et al. Reading a Neural Code , 1991, NIPS.
[12] Joseph J. Atick,et al. Towards a Theory of Early Visual Processing , 1990, Neural Computation.
[13] Christian Jutten,et al. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..
[14] J J Hopfield,et al. Olfactory computation and object perception. , 1991, Proceedings of the National Academy of Sciences of the United States of America.
[15] Ralph Linsker,et al. Local Synaptic Learning Rules Suffice to Maximize Mutual Information in a Linear Network , 1992, Neural Computation.
[16] Ralph Linsker,et al. Deriving Receptive Fields Using an Optimal Encoding Criterion , 1992, NIPS.
[17] Schuster Hg. Learning by maximizing the information transfer through nonlinear noisy neurons and "noise breakdown , 1992 .
[18] Zhaoping Li,et al. Understanding Retinal Color Coding from First Principles , 1992, Neural Computation.
[19] Joseph J. Atick,et al. What Does the Retina Know about Natural Scenes? , 1992, Neural Computation.
[20] Gilles Burel,et al. Blind separation of sources: A nonlinear neural algorithm , 1992, Neural Networks.
[21] John C. Russ,et al. The Image Processing Handbook , 2016, Microscopy and Microanalysis.
[22] Néstor Parga,et al. Information processing by a perceptron in an unsupervised learning task , 1993 .
[23] William Bialek,et al. Statistics of Natural Images: Scaling in the Woods , 1993, NIPS.
[24] Joseph J. Atick,et al. Convergent Algorithm for Sensory Receptive Field Development , 1993, Neural Computation.
[25] A. Norman Redlich,et al. Redundancy Reduction as a Strategy for Unsupervised Learning , 1993, Neural Computation.
[26] Néstor Parga,et al. Duality Between Learning Machines: A Bridge Between Supervised and Unsupervised Learning , 1994, Neural Computation.
[27] Zhaoping Li,et al. Toward a Theory of the Striate Cortex , 1994, Neural Computation.
[28] Zhaoping Li,et al. Efficient stereo coding in the multiscale representation , 1994 .
[29] François Chapeau-Blondeau. Information entropy maximization in the transmission by a neuron nonlinearity , 1994 .
[30] Daniel L. Ruderman,et al. Designing receptive fields for highest fidelity , 1994 .
[31] Ralph Linsker,et al. Sensory Processing and Information Theory , 1994 .
[32] Zhaoping Li,et al. Towards a theory of striate cortex , 1994 .
[33] J. Rospars,et al. Coding of odour quality: roles of convergence and inhibition , 1994 .