Hamiltonian Matrix Strategy for Exponential Synchronization of Neural Networks with Diffusion

In this paper, the problem of exponential synchronization for a class of chaotic neural networks which covers the Hopfield neural networks and cellular neural networks with reaction-diffusion terms and time-varying delays is investigated. A feedback control gain matrix is derived to achieve the state synchronization of two identical neural networks with reaction-diffusion terms, and the synchronization condition can be verified if a certain Hamiltonian matrix with no eigenvalue on the imaginary axis.