Global asymptotically stability of cellular neural networks with time-varying delay

A set of criteria is presented for the global asymptotically stability of delayed cellular neural networks by constructing suitable Lyapunov functionals, introducing many parameters and combining with the elementary inequality technique. Time-delay is frequently encountered in neural networks, and it is often a source of instability and oscillations in a system. It is very important to research the stability of delayed neural network, especially for global asymptotically stability of the neural network with time-varying delay. In the letter, a novel method is proposed in this note for global asymptotically stability of cellular neural networks with time-varying delay. New delay-dependent global asymptotically stability conditions of cellular neural network with time-varying delay is presented by constructing Lyapunov function and using linear matrix inequality (LMI). Finally, numerical examples are given to demonstrate the effect of the proposed method.