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Mixed \(H_{\infty }\) and Passivity Performance for Delayed Conformable Fractional-Order Neural Networks

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Abstract

This article considers the problems of uniform asymptotic stability and mixed \(H_{\infty }\) and passivity performance for conformable fractional-order uncertain neural networks with time delays. We first present a modified conformable fractional-order Razumikhin theorem for conformable fractional-order systems with time delays. Then, we derive some sufficient conditions in terms of linear matrix inequalities conditions to ensure that the considered system is uniform asymptotic stable with mixed \(H_{\infty }\) and passivity performance levels by employing the conformable fractional-order Razumikhin approach. Two simulation examples confirm the correctness of the theoretical results.

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Acknowledgements

The authors would like to thank the editor(s) and anonymous reviewers for their constructive comments which helped to improve the present paper. This research was supported by Project of the TNU-University of Sciences in Vietnam under Grant Number CS2022-TN06-02.

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Authors and Affiliations

  1. Department of Mathematics and Informatics, TNU–University of Sciences, Thainguyen, Vietnam

    Nguyen Thi Thanh Huyen & Mai Viet Thuan

  2. Department of Mathematics, University of Mining and Geology, Hanoi, Vietnam

    Nguyen Truong Thanh

  3. Faculty of Fundamental Science, Hanoi University of Industry, 298 Cau Dien Street, Bac Tu Liem District, Hanoi, Vietnam

    Nguyen Huu Sau

  4. Department of Basic Sciences, Thai Nguyen University of Economics and Business Administration, Thainguyen, Vietnam

    Tran Nguyen Binh

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  1. Nguyen Thi Thanh Huyen
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Correspondence to Mai Viet Thuan.

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Huyen, N.T.T., Thanh, N.T., Sau, N.H. et al. Mixed \(H_{\infty }\) and Passivity Performance for Delayed Conformable Fractional-Order Neural Networks. Circuits Syst Signal Process 42, 5142–5160 (2023). https://doi.org/10.1007/s00034-023-02358-7

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