A probabilistic model of neural networks with static attractors
K. Yamanaka, Michael Uzoma Agu · IEEE Transactions on Systems Man and Cybernetics · 1990
A probabilistic version of the binary Hopfield networks is proposed. Operation of the network is completely parallel, in the sense that evolution of each unit is governed only by its inherent probabilistic law. It is shown that the global state is attracted by one of the equilibria with probability one.>