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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 by using the Lyapunov stability theory, and the synchronization condition can be verified if a certain Hamiltonian matrix with no eigenvalue on the imaginary axis. This condition can avoid solving an algebraic Riccati equation. The results make a preparation for the research about synchronization of delayed neural networks and further the earlier researches. A numerical example illustrates the effectiveness of the results.