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Finite-time projective synchronization of memristor-based delay fractional-order neural networks

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Abstract

This paper mainly investigates the finite-time projective synchronization problem of memristor-based delay fractional-order neural networks (MDFNNs). By using the definition of finite-time projective synchronization, combined with the memristor model, set-valued map and differential inclusion theory, Gronwall–Bellman integral inequality and Volterra-integral equation, the finite-time projective of MDFNNs is achieved via the linear feedback controller. Novel sufficient conditions are obtained to guarantee the finite-time projective synchronization of the drive-response MDFNNs. Besides, we also analyze the feasible region of the settling time. Finally, two numerical examples are given to show the effectiveness of the proposed results.

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Acknowledgements

This paper is supported by the National Key Research and Development Program (Grant No.2016YFB0800602), the National Natural Science Foundation of China (Grant Nos.61472045, 61573067).

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Authors and Affiliations

  1. School of Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Mingwen Zheng, Jinghua Xiao & Hui Zhao

  2. School of Science, Shandong University of Technology, Zibo, 255000, China

    Mingwen Zheng

  3. State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Jinghua Xiao

  4. Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Lixiang Li, Haipeng Peng & Yixian Yang

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  1. Mingwen Zheng
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Correspondence to Lixiang Li.

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Zheng, M., Li, L., Peng, H. et al. Finite-time projective synchronization of memristor-based delay fractional-order neural networks. Nonlinear Dyn 89, 2641–2655 (2017). https://doi.org/10.1007/s11071-017-3613-z

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