Global asymptotic stability of a class of neural networks with time varying delays

This work presents a new sufficient condition for the uniqueness and global asymptotic stability (GAS) of the equilibrium point for a larger class of neural networks with time varying delays. It is shown that the use of a more general type of Lyapunov-Krasovskii functional leads to establish global asymptotic stability of a larger class of delayed neural networks that the neural network model considered in some previous papers.