Analog LSI implementation of self-learning neural networks
暂无分享,去创建一个
[1] Osamu Fujita,et al. A sparse memory-access neural network engine with 96 parallel data-driven processing units , 1995, Proceedings ISSCC '95 - International Solid-State Circuits Conference.
[2] Takashi Morie,et al. An all-analog expandable neural network LSI with on-chip backpropagation learning , 1994, IEEE J. Solid State Circuits.
[3] Hirofumi Shinohara,et al. A 1.2GFLOPS neural network chip exhibiting fast convergence , 1994, Proceedings of IEEE International Solid-State Circuits Conference - ISSCC '94.
[4] Yoshihito Amemiya,et al. A floating-gate analog memory device for neural networks , 1993 .
[5] H. C. Card,et al. Analog CMOS deterministic Boltzmann circuits , 1993 .
[6] Takashi Morie,et al. Deterministic Boltzmann Machine Learning Improved for Analog LSI Implementation , 1993 .
[7] D. Hammerstrom,et al. Neural networks at work , 1993, IEEE Spectrum.
[8] H. Ishiwara. Proposal of Adaptive-Learning Neuron Circuits with High Density Synapse Array of Ferroelectric Thin Films , 1993 .
[9] Robert G. Meyer,et al. Analysis and Design of Analog Integrated Circuits , 1993 .
[10] Tetsuro Itakura,et al. Neuro chips with on-chip back-propagation and/or Hebbian learning , 1992 .
[11] Takashi Morie,et al. Analog VLSI Implementation of Adaptive Algorithms by an Extended Hebbian Synapse Circuit , 1992 .
[12] H. Shinohara,et al. A refreshable analog VLSI neural network chip with 400 neurons and 40 k synapses , 1992, 1992 IEEE International Solid-State Circuits Conference Digest of Technical Papers.
[13] Joshua Alspector,et al. Experimental Evaluation of Learning in a Neural Microsystem , 1991, NIPS.
[14] Pierre Baldi,et al. Contrastive Learning and Neural Oscillations , 1991, Neural Computation.
[15] R. Pinkham,et al. An 11-million Transistor Neural Network Execution Engine , 1991, 1991 IEEE International Solid-State Circuits Conference. Digest of Technical Papers.
[16] Edward A. Rietman,et al. Back-propagation learning and nonidealities in analog neural network hardware , 1991, IEEE Trans. Neural Networks.
[17] Carsten Peterson,et al. Explorations of the mean field theory learning algorithm , 1989, Neural Networks.
[18] Carsten Peterson,et al. A Mean Field Theory Learning Algorithm for Neural Networks , 1987, Complex Syst..
[19] Geoffrey E. Hinton,et al. Learning symmetry groups with hidden units: beyond the perceptron , 1986 .
[20] J J Hopfield,et al. Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.