Global dissipativity in the mean square of stochastic Cohen-Grossberg neural networks with time delays

In this paper, the problem of global dissipativity in the mean square is discussed for stochastic Cohen-Grossberg neural networks with time delays. By constructing general Lyapunov functions, combining with Itô's formula, several sufficient conditions for the global dissipativity in the mean square are derived. Moreover, we give out the estimations of globally attractive sets. Finally, one example is given to show the effectiveness of the proposed criteria.