On the Asymptotic Stability of Non-autonomous Delayed Neural Networks

The global asymptotic stability of non-autonomous delayed neural networks is discussed in this paper. By utilizing a delay differential inequality, we present several sufficient conditions which guarantee the asymptotic stability. Since these conditions do not impose differentiability on delay function, they are less conservative than some established in the earlier references. The results show that this approach is more straightforward and effective for stability analysis compared with the method of Lyapunov functionals which has been successfully applied the in the literature.

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