Global asymptotic stability of a larger class of delayed neural networks
Sabri Arik · 2003
This paper presents some new sufficient conditions for the uniqueness and global asymptotic stability (GAS) of the equilibrium point for a larger class of neural networks with constant time delay. It is shown that the use of a more general type of Lyapunov-Krasovskii functional enables us to establish global asymptotic stability of a larger class of delayed neural networks than those considered in some previous papers.