Global robust dissipativity for integro-differential systems modeling neural networks with delays

In this paper, the global robust dissipativity of integro-differential systems modeling neural networks with time-varying delays are studied. Proper Lyapunov functionals and some analytic techniques are employed to derive the sufficient conditions under which the networks proposed are the global robust dissipativity. The results are shown to improve the previous global dissipativity results derived in the literature. Some examples are given to illustrate the correctness of our results.