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H_∞ output synchronization of directed coupled reaction-diffusion neural networks via event-triggered quantized control

机译:H_∞通过事件触发量化控制输出定向耦合反应扩散神经网络的同步

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By designing a quantized controller based on event trigger, this paper considers the problem of H-infinity output synchronization for coupled neural networks with reaction-diffusion term and directed topology. Firstly, in this hybrid control strategy, the data is sampled in time domain to exclude the Zeno-behavior before judging whether an event is triggered, and then the event-triggered data instead of the sampling data itself is quantized by a logarithmic quantizer. Secondly, some sufficient conditions for H-infinity output synchronization are obtained, in which the dimension of these conditions can be reduced to only depend on the number of neurons, but not on the number of nodes. Finally, a numerical example is given to verify the theoretical results. (C) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:通过基于事件触发设计量化控制器,本文考虑了H-Infinity输出同步与反应扩散术语和定向拓扑的耦合神经网络的问题。 首先,在这种混合控制策略中,在时域中采样数据以在判断事件触发之前排除ZENO行为,然后通过对数量子器量化事件触发数据而不是采样数据本身进行量化。 其次,获得了H-Infinity输出同步的一些充分条件,其中可以减少这些条件的尺寸,仅取决于神经元的数量,而不是在节点的数量上。 最后,给出了数值例子来验证理论结果。 (c)2021年富兰克林学院。 elsevier有限公司出版。保留所有权利。

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    《Journal of the Franklin Institute 》 |2021年第8期| 4458-4482| 共25页
  • 作者单位

    Zhoukou Normal Univ Sch Math & Stat Zhoukou 466001 Peoples R China;

    Xinjiang Univ Coll Math & Syst Sci Urumqi 830046 Peoples R China;

    Xinjiang Univ Coll Math & Syst Sci Urumqi 830046 Peoples R China;

    Xinjiang Univ Coll Math & Syst Sci Urumqi 830046 Peoples R China;

    Zhoukou Normal Univ Sch Math & Stat Zhoukou 466001 Peoples R China;

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