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Robust Stabilization of Memristor-based Coupled Neural Networks with Time-varying Delays

  • Qianhua FuEmail author
  • Jingye Cai
  • Shouming Zhong
Article
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Abstract

The robust stabilization problem of memristor-based coupled neural networks (MNNs) is addressed in this paper. Firstly, the fuzzy model of MNNs is obtained by considering the properties of memristor and corresponding circuit, some predictable assumptions on the boundedness and Lipschitz continuity of activation functions are formulated. Secondly, based on T-S fuzzy theory and Lyapunov-Krasovskii functional method, robust stabilization criteria are derived in form of linear matrix inequalities (LMIs). Finally a numerical example is presented to demonstrate the effectiveness of the proposed robust stabilization criteria, which well supports theoretical results.

Keywords

Coupled neural networks memristor robust stabilization T-S fuzzy time-varying delays 

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Copyright information

© ICROS, KIEE and Springer 2019

Authors and Affiliations

  1. 1.School of Electrical Engineering and Electronic InformationXihua UniversityChengduP. R. China
  2. 2.School of Information and Software EngineeringUniversity of Electronic Science and Technology of ChinaChengduP. R. China
  3. 3.School of Mathematical SciencesUniversity of Electronic Science and Technology of ChinaChengduP. R. China

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