Parallel Random Number Generation for VLSI Systems Using Cellular Automata
IEEE Transactions on Computers
Learning and relearning in Boltzmann machines
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Parallel pseudorandom number generation in GaAs cellular automata for high speed circuit testing
Journal of Electronic Testing: Theory and Applications
Learning in stochastic bit stream neural networks
Neural Networks
Pulsed neural networks
Stochastic bit-stream neural networks
Pulsed neural networks
Stochastic processes
Stochastic Neural Computation I: Computational Elements
IEEE Transactions on Computers
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Doubly stochastic Poisson processes in artificial neural learning
IEEE Transactions on Neural Networks
Compound binomial processes in neural integration
IEEE Transactions on Neural Networks
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Artificial neural networks employing stochastic arithmetic can under certain conditions outperform those based upon conventional radix arithmetic in reduced power dissipation, silicon area and improved fault tolerance. This paper describes limitations due to the inherent variance in the stochastic signals. We introduce and compare two stochastic multiplexing schemes, inter-count and intra-count multiplexing, for accumulating the total inputs to the artificial neurons.