Improving energy relaxation of hopfield network with augmented lagrange multipliers

The convergence property for energy relaxation of Little-Hopfield neural network using the Augmented Lagrange Multipliers is shown to be better than using Hebbian learning. This paper proposes a new method, called the Augmented Lagrange Hopfield method, to improve method of doing logic programming in neural network. In this paper, it has been proven by computer simulations that the new approach provides good solutions.