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

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 stabilit...

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Main Authors: Shimiao Tang, Jiarong Li, Haijun Jiang, Jinling Wang
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/26/3/199
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author Shimiao Tang
Jiarong Li
Haijun Jiang
Jinling Wang
author_facet Shimiao Tang
Jiarong Li
Haijun Jiang
Jinling Wang
author_sort Shimiao Tang
collection DOAJ
description 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.
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spelling doaj.art-3cd4de146bc74686896f4764389ba8312024-03-27T13:36:49ZengMDPI AGEntropy1099-43002024-02-0126319910.3390/e26030199Fixed-Time Aperiodic Intermittent Control for Quasi-Bipartite Synchronization of Competitive Neural NetworksShimiao Tang0Jiarong Li1Haijun Jiang2Jinling Wang3College of Mathematics and System Science, Xinjiang University, Urumqi 830017, ChinaCollege of Mathematics and System Science, Xinjiang University, Urumqi 830017, ChinaSchool of Mathematics and Statistics, Yili Normal University, Yining 835000, ChinaCollege of Mathematics and Statistics, Northwest Normal University, Lanzhou 730070, ChinaThis 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.https://www.mdpi.com/1099-4300/26/3/199competitive neural networkquasi-bipartite synchronizationfixed-time intermittent controlexternal disturbance
spellingShingle Shimiao Tang
Jiarong Li
Haijun Jiang
Jinling Wang
Fixed-Time Aperiodic Intermittent Control for Quasi-Bipartite Synchronization of Competitive Neural Networks
Entropy
competitive neural network
quasi-bipartite synchronization
fixed-time intermittent control
external disturbance
title Fixed-Time Aperiodic Intermittent Control for Quasi-Bipartite Synchronization of Competitive Neural Networks
title_full Fixed-Time Aperiodic Intermittent Control for Quasi-Bipartite Synchronization of Competitive Neural Networks
title_fullStr Fixed-Time Aperiodic Intermittent Control for Quasi-Bipartite Synchronization of Competitive Neural Networks
title_full_unstemmed Fixed-Time Aperiodic Intermittent Control for Quasi-Bipartite Synchronization of Competitive Neural Networks
title_short Fixed-Time Aperiodic Intermittent Control for Quasi-Bipartite Synchronization of Competitive Neural Networks
title_sort fixed time aperiodic intermittent control for quasi bipartite synchronization of competitive neural networks
topic competitive neural network
quasi-bipartite synchronization
fixed-time intermittent control
external disturbance
url https://www.mdpi.com/1099-4300/26/3/199
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AT haijunjiang fixedtimeaperiodicintermittentcontrolforquasibipartitesynchronizationofcompetitiveneuralnetworks
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