Analysis on delay-dependent stability for neural networks with time-varying delays

O. M. Kwon, Ju H. Park, S. M. Lee, E. J. Cha

Research output: Contribution to journalArticlepeer-review

100 Scopus citations

Abstract

This paper considers the problem of delay-dependent stability criteria for neural networks with time-varying delays. First, by constructing a newly augmented Lyapunov-Krasovskii functional, a less conservative stability criterion is established in terms of linear matrix inequalities (LMIs). Second, by proposing a novel activation function condition which has not been considered, a further improved result is proposed. Finally, two numerical examples utilized in other literature are given to show the improvements over the existing ones and the effectiveness of the proposed idea.

Original languageEnglish
Pages (from-to)114-120
Number of pages7
JournalNeurocomputing
Volume103
DOIs
StatePublished - 1 Mar 2013

Keywords

  • Lyapunov method
  • Neural networks
  • Stability
  • Time-varying delays

Fingerprint

Dive into the research topics of 'Analysis on delay-dependent stability for neural networks with time-varying delays'. Together they form a unique fingerprint.

Cite this