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Dynamical analysis of memristor-based fractional-order neural networks with time delay

机译:基于忆阻器的分数阶神经网络的时滞动力学分析

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摘要

In this paper, the memristor-based fractional-order neural networks with time delay are analyzed. Based on the theories of set-value maps, differential inclusions and Filippov's solution, some sufficient conditions for asymptotic stability of this neural network model are obtained when the external inputs are constants. Besides, uniform stability condition is derived when the external inputs are time-varying, and its attractive interval is estimated. Finally, numerical examples are given to verify our results.
机译:本文分析了基于忆阻器的分数阶神经网络的时滞。基于设定值映射,微分包含和Filippov解的理论,当外部输入为常数时,可以获得该神经网络模型渐近稳定性的一些充分条件。此外,当外部输入随时间变化时,导出一致的稳定条件,并估计其吸引间隔。最后,通过数值例子验证了我们的结果。

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