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Further Results on Fixed-Time Cluster Synchronization of Coupled Neural Networks

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Abstract

This paper considers the fixed-time cluster synchronization of nonlinear coupled neural networks. Some novel cost-saving fixed-time controllers are developed to ensure the cluster synchronization for the coupled neural networks with/without disturbances. Different from the traditional fixed-time synchronization controllers containing many nonlinear terms, the newly designed control protocol only holds one power-exponent term. Two numerical examples are provided to illustrate the feasibility of the derived results.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grants No. 62276119 and 61877030, and the Postgraduate Research & Practice Innovation Program of Jiangsu Normal University under Grant No. 2021XKT1399.

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Authors and Affiliations

  1. School of Computer Science & Technology, Jiangsu Normal University, Xuzhou, 221116, Jiangsu, People’s Republic of China

    Rujia Huang & Xiaoyang Liu

  2. Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai, 200240, Jiangsu, People’s Republic of China

    Xiaoyang Liu

  3. School of Mathematics, Southeast University, Nanjing, 210096, Jiangsu, People’s Republic of China

    Jinde Cao

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  1. Rujia Huang
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  2. Xiaoyang Liu
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  3. Jinde Cao
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Correspondence to Xiaoyang Liu.

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Huang, R., Liu, X. & Cao, J. Further Results on Fixed-Time Cluster Synchronization of Coupled Neural Networks. Neural Process Lett 55, 5069–5085 (2023). https://doi.org/10.1007/s11063-022-11081-4

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