Diluted neural networks with adapting and correlated synapses.
We consider the dynamics of diluted neural networks with clipped and adapting synapses. Unlike previous studies, the learning rate is kept constant as the connectivity tends to infinity: the synapses evolve on a time scale intermediate between the quenched and annealing limits and all orders of synaptic correlations must be taken into account. The dynamics is solved by mean-field theory, the order parameter for synapses being a function. We describe the effects, in the double dynamics, due to synaptic correlations.
Mannarelli
M
M
Center of Innovative Technologies for Signal Detection and Processing, Dipartimento di Fisica dell'Università di Bari and INFN, Sezione di Bari, via Amendola 173, 70126 Bari, Italy.
Nardulli
G
G
Stramaglia
S
S
D055592:Biophysical Phenomena; D001703:Biophysics; D007858:Learning / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D013269:Stochastic Processes; D013569:Synapses / Q000502:physiology*