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A New Stability Condition for Uncertain Fuzzy Hopfield Neural Networks with Time-varying Delays

  • Jing Wang
  • Xia Liu
  • Jianjun BaiEmail author
  • Yuanfang Chen
Article
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Abstract

In this paper, the global asymptotic stability of uncertain fuzzy Hopfield neural networks(UFHNNs) with time-varying delays is investigated. Firstly, a new fuzzy Lyapunov function comprising a special line-integral function of fuzzy vector is proposed. Then by using the Wirtinger-based integral inequality to determine the upper bound of the derivative term of the Lyapunov function more accurately, a new stability criterion with less conservatism is derived in the form of linear matrix inequality(LMI). At last, an examples is given to show the effectiveness and superiority of our result.

Keywords

Fuzzy Lyapunov function time-varying delays uncertain fuzzy Hopfield neural networks Wirtinger-based integral inequality 

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Copyright information

© ICROS, KIEE and Springer 2019

Authors and Affiliations

  • Jing Wang
    • 1
  • Xia Liu
    • 2
  • Jianjun Bai
    • 3
    Email author
  • Yuanfang Chen
    • 3
  1. 1.Laiwu Vocational and Technical CollegeLaiwu City, Shandong ProvinceChina
  2. 2.Research Institute of PetroChinaLiaoyang Petrochemical CompanyLiaoning ProvinceChina
  3. 3.Key Lab for IOT and Information Fusion Technology of Zhejiang, Institute of Information and ControlHangzhou Dianzi UniversityHangzhouChina

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