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Quasi-bipartite synchronization of heterogeneous memristive neural networks via pinning control

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Abstract

This paper focuses on quasi-bipartite synchronization of heterogeneous memristive neural networks (MNNs) with cooperative–competitive interactions. Firstly, MNNs with nonidentical uncertain parameters are investigated. A pinning control is adopted to study robust quasi-bipartite synchronization of uncertain MNNs over the signed graph. A sufficient condition is derived for robust quasi-bipartite synchronization. Secondly, a more general heterogeneous MNNs is further discussed over the signed graph. Due to the heterogeneities of the MNNs, quasi-bipartite synchronization is studied and the corresponding sufficient condition is obtained. Additionally, the upper bounds of quasi-bipartite synchronization for two kinds of MNNs are given. Finally, two examples are given to illustrate theoretical results.

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Acknowledgements

This work was supported by the Qing Lan Project of Jiangsu Province of China, the National Natural Science Foundation of China under Grant Nos. 61802201 and 62073172, and the NUPTSF under Grant No. NY220032.

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Authors and Affiliations

  1. School of Science, Nanjing University of Posts and Telecommunications, Nanjing, 210023, Jiangsu, China

    Jiuyu Yang, Zhengxin Wang, Yuanzhen Feng, Yanling Lu & Cong Zheng

  2. Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot), Nanjing University of Posts and Telecommunications, Nanjing, 210023, Jiangsu, China

    Zhengxin Wang, Yanling Lu, Min Xiao & Cong Zheng

  3. School of Automation, Nanjing University of Posts and Telecommunications, Nanjing, 210023, Jiangsu, China

    Min Xiao

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  1. Jiuyu Yang
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Correspondence to Zhengxin Wang.

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Yang, J., Wang, Z., Feng, Y. et al. Quasi-bipartite synchronization of heterogeneous memristive neural networks via pinning control. Neural Comput & Applic 35, 7801–7815 (2023). https://doi.org/10.1007/s00521-022-08087-3

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  • DOI: https://doi.org/10.1007/s00521-022-08087-3

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