Exponential Stability Criterion for Cohen-Grossberg Neural Networks with Time-varying Delay

In this paper, the global exponential stability is investigated for the Cohen-Grossberg neural networks with time-varying delay. By using the appropriate Lyapunov-Krasovskii functional and equivalent descriptor form of the considered system, an LMI-based delay-dependent sufficient condition is obtained to guarantee the exponential stability of the addressed neural networks, which can be checked readily by resorting to the Matlab LMI toolbox. A numerical example is given to show the effectiveness and less conservatism of the obtained methods.