A new nonlinear integro-differential inequality and its application

In this paper, a new nonlinear integro-differential inequality is established. Using the properties of M -cone and a generalization of Barbalat’s lemma, the boundedness and asymptotic behavior for the solution of the inequality are obtained. Applying this nonlinear integro-differential inequality, the invariant and attracting sets for Cohen–Grossberg neural networks with mixed delays are obtained. The results extend and improve the earlier publications. An example is given to illustrate the efficiency of the obtained results.