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pth Moment synchronization of Markov switched neural networks driven by fractional Brownian noise

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Abstract

This paper deals with the pth moment synchronization problem for a type of the stochastic neural networks with Markov switched parameters and driven by fractional Brownian noise (FBNSNN). A method called time segmentation method, very different to the Lyapunov functional approach, has been presented to solve the above problem. Meanwhile, based on the trajectory of error system, associating with infinitesimal operator theory, we propose a sufficient condition of consensus for the drive–response system. The criterion of pth moment exponential stability for FBNSNN can guarantee the synchronization under the designed controller. Finally, two numerical examples and some illustrative figures are provided to show the feasibility and effectiveness for our theoretical results.

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Acknowledgments

This work is partially supported by the Open Research Fund Program of Institute of Applied Mathematics Yangtze University (Grant No. KF1602).

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Authors and Affiliations

  1. School of Information and Mathematics, Yangtze University, Jingzhou, 434023, China

    Xianghui Zhou & Zhi Li

  2. School of Mathematics and Statistics, Anyang Normal University, Anyang, 455000, China

    Jun Yang

  3. College of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai, 201620, China

    Dongbing Tong

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  1. Xianghui Zhou
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  2. Jun Yang
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  3. Zhi Li
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  4. Dongbing Tong
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Correspondence to Xianghui Zhou.

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Zhou, X., Yang, J., Li, Z. et al. pth Moment synchronization of Markov switched neural networks driven by fractional Brownian noise. Neural Comput & Applic 29, 823–836 (2018). https://doi.org/10.1007/s00521-016-2593-0

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  • DOI: https://doi.org/10.1007/s00521-016-2593-0

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