Improved global asymptotically stability of cellular neural networks with time-varying delay

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. In this paper, the global asymptotically stability of cellular neural network with time-varying is investigated. By introducing appropriate Lyapunov functional, new sufficient condition are obtained to ensuring the global asymptotically stability of neural network with time-varying delay. Finally, a numerical example is given to demonstrate the effect of the proposed method.