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Asymptotical synchronization for delayed stochastic neural networks with uncertainty via adaptive control

  • Dongbing Tong
  • Liping Zhang
  • Wuneng Zhou
  • Jun Zhou
  • Yuhua Xu
Article

Abstract

In this paper, the problem of the adaptive synchronization control is considered for neural networks with uncertainty and stochastic noise. Via utilizing stochastic analysis method and linear matrix inequality (LMI) approach, several sufficient conditions to ensure the adaptive synchronization for neural networks are derived. By the adaptive feedback methods, some suitable parameters update laws are found. Finally, a simulation result is provided to substantiate the effectiveness of the proposed approach.

Keywords

Neural networks stochastic noises synchronization control time-delays uncertainty 

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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.School of Electronic and Electrical EngineeringShanghai University of Engineering ScienceShanghaiChina
  2. 2.Department of Electronic EngineeringSchool of Information Science and Technology, Fudan UniversityShanghaiChina
  3. 3.College of Information Sciences and TechnologyDonghua UniversityShanghaiChina
  4. 4.School of FinanceNanjing Audit UniversityJiangsuChina

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