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Collective properties of neural networks: A statistical physics approach. (English) Zbl 0561.92020
The collective properties of neural networks are studied by the application of general methods of statistical mechanics. In a situation like neural network, the construction of Hamiltonians is fraught with difficulties. One way is to simulate the equilibrium of large systems; the other consists in modelling the network as a stochastic process evolving in a Markov manner naturally the evolution equation where its general equilibrium solution offers a way of identifying the Hamiltonian. Several models in vogue in physics including the Ising models are reviewed and adapted to the case of assembly of neurons.
Reviewer: S.K.Srinivasan

MSC:
92F05 Other natural sciences (mathematical treatment)
60K35 Interacting random processes; statistical mechanics type models; percolation theory
92Cxx Physiological, cellular and medical topics
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