Stability analysis on Cohen–Grossberg neural networks with both time-varying and continuously distributed delays

In this paper, the global exponential stability is investigated for a class of Cohen–Grossberg neural networks with time-varying and continuously distributed delays. By using an appropriate Lyapunov–Krasovskii functional and equivalent descriptor form, the sufficient conditions are obtained to guarantee the exponential stability of the addressed system. These conditions are expressed in terms of LMIs and can be checked by resorting to the Matlab LMI toolbox. In addition, the activation functions are of more general descriptions and the derivative of a time-varying delay can take any value, which generalize and further improve those earlier methods. Numerical examples are given to show the reduced conservatism of obtained methods.