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竞争神经网络准二分同步的固定时间非周期间歇控制

Fixed-Time Aperiodic Intermittent Control for Quasi-Bipartite Synchronization of Competitive Neural Networks.

作者信息

Tang Shimiao, Li Jiarong, Jiang Haijun, Wang Jinling

机构信息

College of Mathematics and System Science, Xinjiang University, Urumqi 830017, China.

School of Mathematics and Statistics, Yili Normal University, Yining 835000, China.

出版信息

Entropy (Basel). 2024 Feb 26;26(3):199. doi: 10.3390/e26030199.

DOI:10.3390/e26030199
PMID:38539711
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10969591/
Abstract

This paper concerns a class of coupled competitive neural networks, subject to disturbance and discontinuous activation functions. To realize the fixed-time quasi-bipartite synchronization, an aperiodic intermittent controller is initially designed. Subsequently, by combining the fixed-time stability theory and nonsmooth analysis, several criteria are established to ensure the bipartite synchronization in fixed time. Moreover, synchronization error bounds and settling time estimates are provided. Finally, numerical simulations are presented to verify the main results.

摘要

本文研究一类受干扰且具有不连续激活函数的耦合竞争神经网络。为实现固定时间准二分同步，首先设计了一种非周期间歇控制器。随后，结合固定时间稳定性理论和非光滑分析，建立了若干准则以确保在固定时间内实现二分同步。此外，还给出了同步误差界和调节时间估计。最后，通过数值仿真验证了主要结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/15b1ea67ea41/entropy-26-00199-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/d47c00392264/entropy-26-00199-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/4c765fd76b9e/entropy-26-00199-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/b395a665ac57/entropy-26-00199-g003a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/e8ea5a9fde73/entropy-26-00199-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/15b1ea67ea41/entropy-26-00199-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/d47c00392264/entropy-26-00199-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/4c765fd76b9e/entropy-26-00199-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/b395a665ac57/entropy-26-00199-g003a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/e8ea5a9fde73/entropy-26-00199-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2023/10969591/15b1ea67ea41/entropy-26-00199-g005.jpg

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本文引用的文献

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Projective Synchronization of Delayed Uncertain Coupled Memristive Neural Networks and Their Application.时滞不确定耦合忆阻神经网络的投影同步及其应用
Entropy (Basel). 2023 Aug 21;25(8):1241. doi: 10.3390/e25081241.
2
Quasi-Synchronization of Fractional Multiweighted Coupled Neural Networks via Aperiodic Intermittent Control.基于非周期间歇控制的分数阶多重加权耦合神经网络的准同步
IEEE Trans Cybern. 2024 Mar;54(3):1671-1684. doi: 10.1109/TCYB.2023.3237248. Epub 2024 Feb 9.
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Global synchronization of complex-valued neural networks with unbounded time-varying delays.
具有无界时变时滞的复值神经网络的全局同步。
Neural Netw. 2023 May;162:309-317. doi: 10.1016/j.neunet.2023.02.041. Epub 2023 Mar 6.
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Fixed-time synchronization of discontinuous competitive neural networks with time-varying delays.时变时滞离散竞争神经网络的固定时间同步。
Neural Netw. 2022 Sep;153:192-203. doi: 10.1016/j.neunet.2022.06.002. Epub 2022 Jun 9.
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Lag H synchronization of coupled neural networks with multiple state couplings and multiple delayed state couplings.具有多重状态耦合和多重时滞状态耦合的耦合神经网络的滞后 H 同步。
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Finite-/fixed-time synchronization for Cohen-Grossberg neural networks with discontinuous or continuous activations via periodically switching control.基于周期切换控制的具有间断或连续激活函数的Cohen-Grossberg神经网络的有限时间/固定时间同步
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Finite-time bipartite synchronization of switched competitive neural networks with time delay via quantized control.时滞切换竞争神经网络的有限时间双边同步的量子控制方法。
ISA Trans. 2022 Jun;125:156-165. doi: 10.1016/j.isatra.2021.06.015. Epub 2021 Jun 17.
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Improved Results on Fixed-/Preassigned-Time Synchronization for Memristive Complex-Valued Neural Networks.固定/预分配时间同步的忆阻复值神经网络的改进结果。
IEEE Trans Neural Netw Learn Syst. 2022 Oct;33(10):5542-5556. doi: 10.1109/TNNLS.2021.3070966. Epub 2022 Oct 5.