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Exponential Stability of Delayed High-order Hopfield-type Neural Networks with Diffusion

This paper considers a generalized model of high-order Hopfield-type neural networks with time-varying delays and reaction-diffusion terms. By using the method of Lyapunov function and Halanay's inequality, we investigate the global exponential stability of high-order Hopfield-type neural networks with time-varying delays and reaction-diffusion terms. A sufficient condition for ensuring global exponential stability of these networks is derived, and the estimated exponential convergence rate is also obtained. As an illustration, an numerical example is worked out using the results obtained.