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Anti-synchronization of coupled memristive neutral-type neural networks with mixed time-varying delays via randomly occurring control

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Abstract

In this paper, a class of coupled memristive neural networks of neutral type with mixed time-varying delays via randomly occurring control is studied in order to achieve anti-synchronization. The model of the coupled memristive neural networks of neutral type with mixed time-varying delays is less conservative than those of traditional memristive neural networks. Some criteria are obtained to guarantee the anti-synchronization between the drive system and the response system. Two kinds of randomly occurring memristor-based controllers are designed. The analysis in this paper employs the differential inclusions theory, linear matrix inequalities, and the Lyapunov functional method. In addition, the new proposed results here are very easy to verify and also extend the results of earlier publications. Numerical examples are given to show the effectiveness of our results.

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Acknowledgments

This paper is supported by the National Natural Science Foundation of China (Grant Nos. 61170269, 61573067, 61472045, 61174103), the Beijing Higher Education Young Elite Teacher Project (Grant No. YETP0449), the National Key Technologies R&D Program of China under Grant 2015BAK38B01, the Aerospace Science Foundation of China under Grant 2014ZA74001, the Fundamental Research Funds for the Central Universities, the Asia Foresight Program under NSFC Grant (Grant No. 61411146001), and the Beijing Natural Science Foundation (Grant No. 4142016)

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Authors and Affiliations

  1. School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing, 100083, China

    Weiping Wang

  2. 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

  3. School of Mechanical Engineering, North China University of Water Resources and Electric Power, Zhengzhou, 450045, China

    Weinan Wang

  4. Potsdam Institute for Climate Impact Research, 14473, Potsdam, Germany

    Jürgen Kurths

  5. National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Yixian Yang

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

    Jinghua Xiao

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  1. Weiping Wang
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  2. Lixiang Li
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  3. Haipeng Peng
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  4. Weinan Wang
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  5. Jürgen Kurths
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  6. Jinghua Xiao
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  7. Yixian Yang
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Correspondence to Lixiang Li.

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Wang, W., Li, L., Peng, H. et al. Anti-synchronization of coupled memristive neutral-type neural networks with mixed time-varying delays via randomly occurring control. Nonlinear Dyn 83, 2143–2155 (2016). https://doi.org/10.1007/s11071-015-2471-9

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  • DOI: https://doi.org/10.1007/s11071-015-2471-9

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