Asymmetric Sherrington-Kirkpatrick model of neural networks with random neuronal threshold.

Abstract

The random asymmetric Sherrington-Kirkpatrick model of neural networks with random neuronal thresholds has been investigated by a Langevin-dynamics approach. It is shown that in the presence of Gaussian random «external» fields with zero mean and variance Δ, the spin-glass transition disappears and the Edwards-Anderson order parameter remains finite at all temperatures T. The replica-symmetric phase is separated from the symmetry-breaking phase by a line of instability in the (T,Δ) plane