Cohen and Grossberg (1983) studied an almost gradient system of ordinary differential equations with application to neural networks and used a Liapunov function, together with an invariance principle, to show that some equilibrium points attract solutions. Independently, Hopfield (1984) modeled a neural network by means of a system of ordinary differential equations which turn out to be a speci...

In this article, we consider a model that describes the dynamics of Cohen-Grossberg neural networks with unbounded distributed delays, whose state variable are governed by stochastic non-linear integro-differential equations. Without assuming the smoothness, monotonicity and boundedness of the activation functions, by constructing suitable Lyapunov functional, employing the semi-martingale conv...

<p style='text-indent:20px;'>This research paper deals with the investigation of global robust stability results for Cohen-Grossberg neural networks involving multiple constant time delays. The activation functions in this network model are supposed to be set non-decreasing slope-bounded nonlinear and uncertainties parameters considered have bounded upper norms. By employing a proper posi...