Passivity and Synchronization for Fuzzy Coupled Reaction–Diffusion Neural Networks With Multiweights

This article is concerned with passivity and synchronization for fuzzy coupled reaction-diffusion neural networks (FCRDNNs) with multistate couplings or multiple spatial-diffusion couplings. First, by utilizing an adaptive state feedback controller, several passivity criteria for the FCRDNNs with multistate couplings are obtained. Moreover, a sufficient condition to guarantee the synchronization for the multistate coupled FCRDNNs is also given on the basis of the devised adaptive state feedback control scheme. Additionally, the problems of passivity and synchronization are also addressed for the FCRDNNs with multiple spatial-diffusion couplings by employing the adaptive control technique and Lyapunov functional method. Finally, two numerical examples are presented to validate the effectiveness of the devised adaptive control schemes.

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Publication Details

Journal
IEEE Transactions on Cybernetics
Published
2025-09-03
DOI
https://doi.org/10.1109/tcyb.2025.3600921
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Passivity and Synchronization for Fuzzy Coupled Reaction–Diffusion Neural Networks With Multiweights

Shun‐Yan Ren, Tingwen Huang, Jin-Liang Wang, Xinyu Zhao
IEEE Transactions on Cybernetics
Neural Networks and Applications
article

Passivity and Synchronization for Fuzzy Coupled Reaction–Diffusion Neural Networks With Multiweights

Shun‐Yan Ren, Tingwen Huang, Jin-Liang Wang, Xinyu Zhao
article en

Abstract

This article is concerned with passivity and synchronization for fuzzy coupled reaction-diffusion neural networks (FCRDNNs) with multistate couplings or multiple spatial-diffusion couplings. First, by utilizing an adaptive state feedback controller, several passivity criteria for the FCRDNNs with multistate couplings are obtained. Moreover, a sufficient condition to guarantee the synchronization for the multistate coupled FCRDNNs is also given on the basis of the devised adaptive state feedback control scheme. Additionally, the problems of passivity and synchronization are also addressed for the FCRDNNs with multiple spatial-diffusion couplings by employing the adaptive control technique and Lyapunov functional method. Finally, two numerical examples are presented to validate the effectiveness of the devised adaptive control schemes.

IEEE Transactions on CyberneticsVol. 55(12)
Shenzhen University (CN), Tiangong University (CN), Guangdong Institute of Intelligent Manufacturing (CN), Shenzhen Technology University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 88%
Neural Networks and Applications
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