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Fixed-time passification analysis of interconnected memristive reaction-diffusion neural networks
IEEE Transactions on Network Science and Engineering ( IF 6.6 ) Pub Date : 2020-07-01 , DOI: 10.1109/tnse.2019.2954463
Zengyun Wang , Jinde Cao , Guoping Lu , Mahmoud Abdel-Aty

This article deals with fixed-time passification problem of interconnected networks composed of multiple memristive reaction-diffusion subsystems. Different from the finite-time passivity proposed by Wang, Zhang, et al. (2018), a novel concept of fixed-time passivity/passification is proposed by using upper right Dini derivative, where the settling time is independent on initial value. Next, by designing an appropriate controller and utilizing inequality technique, we put forward several sufficient conditions to guarantee the fixed-time passification of the interconnected memristive reaction-diffusion neural networks (MRDNNs). Furthermore, a fixed-time synchronization criterion is proposed for interconnected MRDNNs. The fixed-time passivity/passification of interconnected MRDNNs has important practical significance in the design and implementation of neural network circuits. Finally, a numerical example is presented to substantiate the correctness of the theoretical results.

中文翻译:

互连忆阻反应扩散神经网络的固定时间钝化分析

本文处理由多个忆阻反应扩散子系统组成的互连网络的固定时间传递问题。与 Wang、Zhang 等人提出的有限时间被动性不同。(2018),通过使用右上角的 Dini 导数提出了固定时间被动/钝化的新概念,其中稳定时间与初始值无关。接下来,通过设计合适的控制器并利用不等式技术,我们提出了几个充分条件来保证互连的忆阻反应扩散神经网络(MRDNN)的固定时间传递。此外,还为互连的 MRDNN 提出了固定时间同步准则。相互连接的MRDNNs的固定时间无源/无源化在神经网络电路的设计和实现中具有重要的实际意义。最后,给出了一个数值例子来证实理论结果的正确性。
更新日期:2020-07-01
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