Hopfield Network

Abstract

Attractor neural network; Binary neural network; Equilibrium neural network; Recurrent neural network Definition Hopfield model was originally introduced as the representation of a physical system, whose state in a given time is defined by a vector X(t) = {X 1 (t),.. .,X N (t)}, with a large number of locally stable states in its phase space, namely, X a , X b ,.. .., also called attractors. Starting from some initial condition within the basin of attraction of one of these minima, that is, X(0) = X a + D, the dynamics leads the system toward this minimum, that is, X(t ! 1) % X a. The model provides a rule