Global asymptotically robust 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, especially for global asymptotically robust stability of the neural network with time-varying delay. In the letter, a novel method is proposed in this note for global asymptotically robust stability of cellular neural networks with time-varying delay. New delay-dependent global asymptotically robust 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.