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Global Mittag-Leffler Synchronization for Fractional-Order BAM Neural Networks with Impulses and Multiple Variable Delays via Delayed-Feedback Control Strategy

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Abstract

This paper is concerned with the global Mittag-Leffler synchronization schemes for the Caputo type fractional-order BAM neural networks with multiple time-varying delays and impulsive effects. Based on the delayed-feedback control strategy and Lyapunov functional approach, the sufficient conditions are established to ensure the global Mittag-Leffler synchronization, which are described as the algebraic inequalities associated with the network parameters. The control gain constants can be searched in a wider range following the proposed synchronization conditions. The obtained results are more general and less conservative. A numerical example is also presented to illustrate the feasibility and effectiveness of the theoretical results based on the modified predictor–corrector algorithm.

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Author information

Authors and Affiliations

  1. State Key Laboratory of Mechanics and Control of Mechanical Structures, Institute of Nano Science and Department of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing, 210018, China

    Renyu Ye & Xinsheng Liu

  2. School of Mathematics and Computation Science, Anqing Normal University, Anqing, 246133, China

    Hai Zhang

  3. School of Mathematics, Southeast University, Nanjing, 210096, China

    Jinde Cao

  4. School of Electrical Engineering, Nantong University, Nantong, 226000, China

    Jinde Cao

Authors
  1. Renyu Ye
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  2. Xinsheng Liu
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  3. Hai Zhang
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  4. Jinde Cao
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Corresponding author

Correspondence to Hai Zhang.

Additional information

This work is jointly supported by the National Natural Science Fund of China (11301308, 61573096, 61272530, 61374183), the Fund of Jiangsu Provincial Key Laboratory of Networked Collective Intelligence (BM2017002), the 333 Engineering Fund of Jiangsu Province of China (BRA2015286), the Natural Science Fund of Anhui Province of China (1608085MA14), the Key Project of Natural Science Research of Anhui Higher Education Institutions of China (gxyqZD2016205, KJ2015A152), and the Natural Science Youth Fund of Jiangsu Province of China (BK20160660).

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Ye, R., Liu, X., Zhang, H. et al. Global Mittag-Leffler Synchronization for Fractional-Order BAM Neural Networks with Impulses and Multiple Variable Delays via Delayed-Feedback Control Strategy. Neural Process Lett 49, 1–18 (2019). https://doi.org/10.1007/s11063-018-9801-0

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  • DOI: https://doi.org/10.1007/s11063-018-9801-0

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