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Adaptive Finite-Time Synchronization of Inertial Neural Networks with Time-Varying Delays via Intermittent Control

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Neural Information Processing (ICONIP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11307))

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Abstract

In this paper, the adaptive finite-time synchronization is investigated for inertial neural networks with time-varying delays. The second-order inertial systems can be transformed into two first-order differential systems by selecting the appropriate variable substitution. Using the adaptive periodically intermittent controllers, the slave system can realize synchronization with the master system in finite time. By the several differential inequalities and finite-time stability theory, some simple finite-time synchronization criteria for an array of inertial neural networks are derived. A numerical example is finally provided to illustrate the effectiveness of the obtained theoretical results.

Y. Yang—This work was supported by the Natural Science Foundation of Jiangsu Province of China under Grant No. BK20170171, BK20161126.

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Authors and Affiliations

  1. School of Science, Wuxi Engineering Research Center for Biocomputing, Jiangnan University, Wuxi, 214122, People’s Republic of China

    Lin Cheng, Yongqing Yang, Xianyun Xu & Xin Sui

Authors
  1. Lin Cheng
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  2. Yongqing Yang
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  3. Xianyun Xu
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  4. Xin Sui
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Corresponding author

Correspondence to Yongqing Yang .

Editor information

Editors and Affiliations

  1. The Chinese Academy of Sciences, Beijing, China

    Long Cheng

  2. City University of Hong Kong, Kowloon, Hong Kong

    Andrew Chi Sing Leung

  3. Kobe University, Kobe, Japan

    Seiichi Ozawa

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Cheng, L., Yang, Y., Xu, X., Sui, X. (2018). Adaptive Finite-Time Synchronization of Inertial Neural Networks with Time-Varying Delays via Intermittent Control. In: Cheng, L., Leung, A., Ozawa, S. (eds) Neural Information Processing. ICONIP 2018. Lecture Notes in Computer Science(), vol 11307. Springer, Cham. https://doi.org/10.1007/978-3-030-04239-4_15

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  • DOI: https://doi.org/10.1007/978-3-030-04239-4_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04238-7

  • Online ISBN: 978-3-030-04239-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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