Stability analysis of neutral type neural networks with mixed time-varying delays using triple-integral and delay-partitioning methods.

Journal: ISA transactions
Published Date:

Abstract

This paper investigates the asymptotical stability problem for a class of neutral type neural networks with mixed time-varying delays. The system not only has time-varying discrete delay, but also distributed delay, which has never been discussed in the previous literature. Firstly, improved stability criteria are derived by employing the more general delay partitioning approach and generalizing the famous Jensen inequality. Secondly, by constructing a newly augmented Lyapunov-Krasovskii functionals, some less conservative stability criteria are established in terms of linear matrix inequalities (LMIs). Finally, four numerical examples are given to illustrate the effectiveness and the advantage of the proposed main results.

Authors

  • Kaibo Shi
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China. Electronic address: skbs111@163.com.
  • Hong Zhu
    Co-Innovation Center for the Sustainable Forestry in Southern China; Cerasus Research Center; College of Biology and the Environment, Nanjing Forestry University, Nanjing, China.
  • Shouming Zhong
    School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China; Key Laboratory for Neuroinformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China.
  • Yong Zeng
    a College of Pharmacy , Chengdu University of Traditional Chinese Medicine , Chengdu , P.R. China.
  • Yuping Zhang
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China.
  • Wenqin Wang
    School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China.