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Pinning Adaptive and Exponential Synchronization of Fractional-Order Uncertain Complex Neural Networks with Time-Varying Delays

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Abstract

This paper investigates the adaptive and exponential synchronization control problem of fractional-order complex neural networks (FOCNN) with uncertain and time-varying delays. Based on the stability theorem of fractional-order dynamics system, an adaptive pinning controller is designed to achieve the asymptotic synchronization of uncertain FOCNN under the corresponding update law, which is only dependent on the states of complex neural networks. Further, some sufficient criteria are derived to ensure exponential synchronization of the derive system and response system by utilizing the Lyapunov stability theory. Finally, the effectiveness of the proposed theoretical results are demonstrated by two numerical examples of uncertain FOCNN with time-varying delays.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (61603107; 61863007). Guangxi Natural Science Foundation (2015GXNSFAA139297) and Guangxi Key Laboratory of Automatic Detecting Technology and Instruments (YQ16108).

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Authors and Affiliations

  1. College of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, People’s Republic of China

    Xiru Wu

  2. Changsha University of Science and Technology, Changsha, 410004, Hunan, People’s Republic of China

    Lihong Huang

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  1. Xiru Wu
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  2. Lihong Huang
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Correspondence to Xiru Wu.

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Wu, X., Huang, L. Pinning Adaptive and Exponential Synchronization of Fractional-Order Uncertain Complex Neural Networks with Time-Varying Delays. Neural Process Lett 50, 2373–2388 (2019). https://doi.org/10.1007/s11063-019-10014-y

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