Design of state estimator for switched hopfield neural networks with time-delay

Research output: Contribution to journalArticle

Abstract

In this paper, the delay-dependent state estimation problem for switched Hopfield neural networks with time-delay is investigated. Based on the Lyapunov-Krasovskii stability theory, a new delay-dependent state estimator for switched Hopfield neural networks is established to estimate the neuron states through available output measurements such that the estimation error system is asymptotically stable. The gain matrix of the proposed estimator is characterized in terms of the solution to a linear matrix inequality (LMI), which can be checked readily by using some standard numerical packages. An illustrative example is given to demonstrate the effectiveness of the proposed state estimator.

Original languageEnglish
Pages (from-to)657-666
Number of pages10
JournalJournal of Circuits, Systems and Computers
Volume20
Issue number4
DOIs
Publication statusPublished - 2011 Jun 1
Externally publishedYes

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Keywords

  • Hopfield neural networks
  • linear matrix inequality (LMI)
  • LyapunovKrasovskii stability theory
  • State estimation
  • switched systems

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Hardware and Architecture

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