Stability analysis of Cohen–Grossberg neural networks with time-varying and distributed delays

In this paper, the global exponential stability is investigated for the Cohen–Grossberg neural networks with time-varying and distributed delays. By using a novel Lyapunov–Krasovskii functional and equivalent descriptor form of addressed system, the delay-dependent sufficient conditions are obtained to guarantee the exponential stability of the considered system. These conditions are expressed in terms of LMIs, and can be checked by resorting to the Matlab LMI toolbox. In addition, the proposed stability criteria do not require the monotonicity of the activation functions and the derivative of a time-varying delay being less than 1, which generalize and improve those earlier methods. Finally, numerical examples are given to show the reduced conservatism of the obtained methods.