H State Estimation for Stochastic Markovian Jumping Neural Network with Time-Varying Delay and Leakage Delay

  • Ya Jun Li*
  • , Zhao Wen Huang
  • , Jing Zhao Li
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The H state estimation problem for a class of stochastic neural networks with Markovian jumping parameters and leakage delay is investigated in this paper. By employing a suitable Lyapunov functional and inequality technic, the sufficient conditions for exponential stability as well as prescribed H norm level of the state estimation error system are proposed and verified, and all obtained results are expressed in terms of strict linear matrix inequalities (LMIs). Examples and simulations are presented to show the effectiveness of the proposed methods, at the same time, the effect of leakage delay on stability of neural networks system and on the attenuation level of state estimator are discussed.

Original languageEnglish
Pages (from-to)329-340
Number of pages12
JournalInternational Journal of Automation and Computing
Volume16
Issue number3
DOIs
StatePublished - 1 Jun 2019
Externally publishedYes

Keywords

  • H filtering state estimation
  • Markovian jump
  • exponential stability
  • leakage delay
  • linear matrix inequality (LMI)
  • neural networks
  • time-varying delay

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