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Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy

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  • Jin-E Zhang
  • Huan Liu

Abstract

This paper proposes the event-triggered strategy (ETS) for multiple neural networks (NNs) with parameter uncertainty and time delay. By establishing event-triggered mechanism and using matrix inequality techniques, several sufficient criteria are obtained to ensure global robust exponential synchronization of coupling NNs. In particular, the coupling matrix need not be the Laplace matrix in this paper. In addition, the lower bounds of sampling time intervals are also found by the established event-triggered mechanism. Eventually, three numerical examples are offered to illustrate the obtained results.

Suggested Citation

  • Jin-E Zhang & Huan Liu, 2019. "Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy," Complexity, Hindawi, vol. 2019, pages 1-16, November.
    • Handle: RePEc:hin:complx:7672068
    DOI: 10.1155/2019/7672068
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    References listed on IDEAS

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    1. Mingwen Zheng & Lixiang Li & Haipeng Peng & Jinghua Xiao & Yixian Yang & Hui Zhao & Jingfeng Ren, 2016. "Finite-time synchronization of complex dynamical networks with multi-links via intermittent controls," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-12, February.
    2. Mingwen Zheng & Lixiang Li & Haipeng Peng & Jinghua Xiao & Yixian Yang & Hui Zhao & Jingfeng Ren, 2016. "Finite-time synchronization of complex dynamical networks with multi-links via intermittent controls," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-12, February.
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