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Finite-Time Stabilization for Static Neural Networks with Leakage Delay and Time-Varying Delay

  • Xiaoyu Zhang
  • Yuan YuanEmail author
  • Xiaodi LiEmail author
Article

Abstract

The problem of finite-time stabilization (FTS) for static neural networks (SNNs) with leakage delay and time-varying delay is investigated in this paper. By introducing an auxiliary function and utilizing the Lyapunov stability theory, we derive some sufficient criteria for FTS in terms of linear matrix inequalities (LMIs). Two feedback controllers are designed based on two different Lyapunov functions, which can be easily solved via MATLAB LMI toolbox, to guarantee the FTS for the SNNs. Finally, two numerical examples are given to illustrate the efficiency of our results.

Keywords

Finite-time stability Static neural networks Time-varying delay Leakage delay Linear matrix inequality (LMI) 

Notes

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Mathematics and StatisticsShandong Normal UniversityJi’nanPeople’s Republic of China
  2. 2.Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information EngineeringSouthwest UniversityChongqingPeople’s Republic of China
  3. 3.Department of Mathematics and StatisticsMemorial University of NewfoundlandSt. John’sCanada

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