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Complex dynamics and stability of Hopfield neural networks with delays

机译:具有时滞的Hopfield神经网络的复杂动力学和稳定性

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In this paper, by utilising the Lyapunov functional method, we analyse the global asymptotic stability of Hopfield neural networks with delays. We obtain some new sufficient conditions to ensure the global asymptotic stability of the model being independent of delays. By using the Lyapunov second method for special cases, we also get that the equilibrium of the system is locally asymptotically stable when the delay is under a critical value; and when the delay is equal to this value, Hopf bifurcation will occur and the equilibrium is unstable; and when the delay is above the critical value, the system will demonstrate complex dynamics. Finally, numerical simulations are presented to verify the analytical results.
机译:本文利用Lyapunov函数方法,分析了具有时滞的Hopfield神经网络的全局渐近稳定性。我们获得了一些新的充分条件,以确保模型的全局渐近稳定性与延迟无关。通过在特殊情况下使用Lyapunov第二方法,我们还得到了当延迟低于临界值时,系统的平衡是局部渐近稳定的。当延迟等于该值时,将发生Hopf分叉,并且平衡不稳定。当延迟超过临界值时,系统将展示出复杂的动态特性。最后,通过数值模拟验证了分析结果。

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