A New Sufficient Condition for Global Robust Stability of Delayed Neural Networks

Abstract

In this paper, by using Lyapunov stability theorems, we present a new sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for delayed neural networks. This condition basically establishes a relationship between the network parameters of the neural system. The obtained condition can be easily verified as it is in terms of the network parameters only. Some illustrative numerical examples are also given to compare our result with the previous robust stability results derived in the literature.