title: Diluted neural networks with adapting and correlated synapses.
abstract: 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.
authors.affiliation: 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.
authors.forename: M
authors.initials: M
authors.lastname: Mannarelli
authors.forename: G
authors.initials: G
authors.lastname: Nardulli
authors.forename: S
authors.initials: S
authors.lastname: Stramaglia
mesh_terms: D055592:Biophysical Phenomena; D001703:Biophysics; D007858:Learning / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D013269:Stochastic Processes; D013569:Synapses / Q000502:physiology*