Neural networks with fast time-variation of synapses
Joaquı́n J. Torres, Pedro L. Garrido, Joaquín Marro · Journal of Physics A Mathematical and General · 1997
We study a kinetic neural network in which the intensity of synaptic couplings varies on a timescale of order compared with that for neuron variations. We describe some exact and mean-field results for . This includes, for example, the Hopfield model with random fluctuations of synapse intensities such that neurons couple each other, on average, according to the Hebbian learning rule. The consequences of such fluctuations on the performance of the network are analysed in detail for some specific choices of the rate and fluctuation distribution, including the case in which couplings are asymmetric.