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Finite-Time Synchronization of Complex-Valued Neural Networks with Multiple Time-Varying Delays and Infinite Distributed Delays

  • Yanjun Liu
  • Yu Qin
  • Junjian HuangEmail author
  • Tingwen Huang
  • Xinbo Yang
Article
  • 52 Downloads

Abstract

This paper investigates finite-time synchronization of complexed-valued neural networks with multiple time-varying delays and infinite distributed delays. By separating the complex-valued neural networks into the real and the imaginary parts, the corresponding equivalent real-valued systems are obtained. Some sufficient conditions are derived for finite-time synchronization of the drive-response system based on the new Lyapunov–Krasovskii function and the new analysis techniques. Numerical examples demonstrate the effectiveness of the theoretical results.

Keywords

Finite-time synchronization Complexed-valued neural networks Multiple time-varying delays Infinite distributed delays Lyapunov–Krasovskii function 

Notes

Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (Grant No. 61403050), the science and technology commission project of Chongqing (cstc2017jcyjA1082, cstc2018jcyjAX0810), the Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJ1501412, KJ1601401, KJ1601410), and the Foundation of CQUE (KY201702A,KY201720B).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mathematical ScienceNankai UniversityTianjinChina
  2. 2.Key Laboratory of Machine Perception and Childrens Intelligence DevelopmentChongqing University of EducationChongqingChina
  3. 3.Texas A&M University at QatarDohaQatar

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