Asymptotical stability criteria for Cohen-Grossberg neural networks with time-varying delay

The global stability of Cohen-Grossberg neural networks with time-varying delay is investigated and a delay-dependent stability criterion is obtained in terms of LMI by choosing a novel Lyapunov-Krasovskii functional, introducing the equivalent descriptor form of addressed systems and employing some free-weighting matrices. The derivative of the time-varying delay has an upper limitation but not necessarily more than 1 and the activation functions are of more general descriptions, which generalize those present results. One numerical example illustrates that the obtained method is an improvement over the earlier ones.