PERSPECTIVES FOR MONTE CARLO SIMULATIONS ON THE CNN UNIVERSAL MACHINE

DOI10.1142/S0129183106009230zbMath1107.82043arXivphysics/0603121MaRDI QIDQ5481845

M. Ercsey-Ravasz, Zoltán Néda, Tamás Roska

Publication date: 24 August 2006

Published in: International Journal of Modern Physics C (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/physics/0603121

zbMATH Keywords

Monte Carlo simulationsrandom number generatorCellular Neural Networks

Mathematics Subject Classification ID

Neural nets applied to problems in time-dependent statistical mechanics (82C32)

Related Items (5)

Statistical physics on cellular neural network computers ⋮ Stochastic bitstream‐based CNN and its implementation on FPGA ⋮ MODELING A NONLINEAR LIQUID LEVEL SYSTEM BY CELLULAR NEURAL NETWORKS ⋮ Cellular neural networks for NP-hard optimization ⋮ Cellular Automata with Random Memory and Its Implementations

Cites Work

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• Cellular neural networks: theory
• The CNN paradigm
• Current-mode techniques for the implementation of continuous- and discrete-time cellular neural networks
• The CNN universal machine: an analogic array computer

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