Improved delay-dependent stability analysis for uncertain stochastic neural networks with time-varying delay

Fang Liu, Min Wu*, Yong He, Ryuichi Yokoyama

*この研究の対応する著者

研究成果: Article査読

7 被引用数 (Scopus)

抄録

This paper focuses on the problem of delay-dependent robust stability analysis for a class of uncertain stochastic neural networks with time-varying delay by employing improved free-weighting matrix method. Taking the relationship among the time-varying delay, its upper bound and their difference into account and using Itô's differential formula, some improved LMI-based delay-dependent stability criteria for stochastic neural networks are obtained without ignoring any terms, which guarantee systems globally robustly stochastically stable in the mean square. Finally, three numerical examples are given to demonstrate the effectiveness and the benefits of the proposed method.

本文言語English
ページ(範囲)441-449
ページ数9
ジャーナルNeural Computing and Applications
20
3
DOI
出版ステータスPublished - 2011 4月

ASJC Scopus subject areas

  • 人工知能
  • ソフトウェア

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