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Exponential stability and synchronization of Memristor-based fractional-order fuzzy cellular neural networks with multiple delays

机译:具有多个延迟的基于Memristor的分数阶模糊蜂窝神经网络的指数稳定性与同步

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摘要

The stability and synchronization problems are addressed in this study for the memristor-based fractional-order fuzzy cellular neural networks with multiple delays. By using the Laplace transform method, fractional-order calculus approach and the method of complex function, three exponential sta-bility criteria are derived. Compared with the existing results of the above system, the novel exponentially stable and synchronization conditions are first proposed. The obtained results can be applied not only to fractional-order systems, but also to integer-order systems. A two-dimension example and a three-dimension example and a practical example are given to illustrate the validity and merits. (c) 2020 Elsevier B.V. All rights reserved.
机译:本研究在该研究中解决了具有多个延迟的忆阻的分数阶模糊蜂窝网络神经网络的稳定性和同步问题。通过使用拉普拉斯变换方法,分数阶微积分和复杂功能的方法,推导出三个指数的STA效力标准。与上述系统的现有结果相比,首先提出了新颖的指数稳定和同步条件。所获得的结果不仅可以应用于分数阶系统,而且可以应用于整数阶系统。给出了两个尺寸示例和三维示例和一个实际的例子来说明有效性和优点。 (c)2020 Elsevier B.v.保留所有权利。

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