Synchronization of Delayed Inertial Cohen—Grossberg Neural Networks Under Adaptive Feedback Controller

Abstract

This paper investigates the issue on adaptive synchronization of delayed inertial Cohen—Grossberg neural networks (ICGNNs). By adopting the method of variable transformation, the addressed model, which includes the so-called inertial term, is transformed into first-order differential equations. On the basis of the well-known invariant principle of functional differential equations, a novel and analytic scheme which ensures the adaptive synchronization between the drive-response system is proposed in component form. It is worth mentioning that we only need to impose one controller to the spilt systems to realize the adaptive synchronization, which is of less conservatism. At the end of this paper, a numerical example is provided to verify the feasibility of the derived theoretical results. The established figures validate that the numerical simulations coincide well with the developed theoretical results.