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Analysis and pinning control for passivity and synchronization of multiple derivative coupled reaction diffusion neural networks

机译:多导数耦合反应扩散神经网络的无源性和同步分析与钉扎控制

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摘要

In this paper, a class of multiple derivative coupled reaction-diffusion neural networks with and without parameter uncertainties is investigated. Firstly, we analyze the passivity and synchronization of the proposed network models and derive several criteria based on inequality techniques. Furthermore, a pinning control strategy is also developed to ensure that the proposed networks can achieve passivity and synchronization. Finally, a numerical example is presented to verify the effectiveness of the obtained criteria. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:本文研究了一类带有和不带有参数不确定性的多导数耦合反应扩散神经网络。首先,我们分析了所提出的网络模型的无源性和同步性,并基于不等式技术推导了一些标准。此外,还开发了一种钉扎控制策略,以确保建议的网络可以实现无源性和同步。最后,给出了一个数值例子来验证所获得标准的有效性。 (C)2019富兰克林研究所。由Elsevier Ltd.出版。保留所有权利。

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    《Journal of the Franklin Institute》 |2020年第2期|1221-1252|共32页
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    Tiangong Univ Sch Comp Sci & Technol Tianjin Key Lab Autonomous Intelligence Technol & Tianjin 300387 Peoples R China;

    Tiangong Univ Sch Comp Sci & Technol Tianjin Key Lab Autonomous Intelligence Technol & Tianjin 300387 Peoples R China|Linyi Univ Sch Informat Sci & Technol Linyi 276005 Shandong Peoples R China;

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  • 入库时间 2022-08-18 05:22:33

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