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Quasi-projective Synchronization Analysis of Delayed Caputo-Type BAM Neural Networks in the Complex Field

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Abstract

This article analyzes the quasi-projective synchronization (QPS) issues of delayed Caputo-type BAM neural networks in the complex field. In order to facilitate calculation and realize QPS, the non-decomposition method is adopted. Moreover, a novel lemma in the form of algebraic inequality is established based on the Laplace transform, which makes it more convenient to deal with the delay term. Applying the proposed lemma, inequality techniques and Lyapunov method, some criteria of QPS are obtained via the designed different controllers. Meanwhile, the error bound is effectively derived. Eventually, the rationality of the gained criteria is tested by two simulations.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (61833005) and the Natural Science Foundation of Anhui Province of China (1908085MA01).

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Authors and Affiliations

  1. School of Mathematics and Physics, Anqing Normal University, Anqing, 246133, People’s Republic of China

    Xinbin Chen, Hai Zhang, Renyu Ye & Qinyun Lu

  2. School of Mathematics, Southeast University, Nanjing, 211189, People’s Republic of China

    Jinde Cao

  3. Yonsei Frontier Lab, Yonsei University, Seoul, 03722, South Korea

    Jinde Cao

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  1. Xinbin Chen
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  2. Hai Zhang
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  3. Renyu Ye
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  4. Qinyun Lu
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Contributions

XC: Writing-original draft, Software. HZ: Conceptualization, Methodology. RY: Methodology, Writing-review & editing. QL: Validation, Writing-review & editing. JC: Supervision, Project administration.

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Correspondence to Hai Zhang.

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Chen, X., Zhang, H., Ye, R. et al. Quasi-projective Synchronization Analysis of Delayed Caputo-Type BAM Neural Networks in the Complex Field. Neural Process Lett 55, 7469–7492 (2023). https://doi.org/10.1007/s11063-023-11269-2

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