Global exponential stability of high order Hopfield type neural networks

This paper studies the problem of global exponential stability for a class of high order Hopfield type neural networks. By utilizing Lyapunov functions, several sufficient conditions for the global exponential stability of equilibrium point are obtained. The exponential convergence rate of the equilibrium point is also estimated. As a special case, several new criteria on global exponential stability for the corresponding first order Hopfield neural networks are obtained. Those criteria generalize some of the recent results reported in the literature.