Stability analysis of neural networks with interval time-varying delays

Yi You Hou, Teh Lu Liao, Chang Hua Lien, Jun Juh Yan

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

The global exponential stability is investigated for neural networks with interval time-varying delays. Based on the Leibniz-Newton formula and linear matrix inequality technique, delay-dependent stability criteria are proposed to guarantee the exponential stability of neural networks with interval time-varying delays. Some numerical examples and comparisons are provided to show that the proposed results significantly improve the allowable upper and lower bounds of delays over some existing ones in the literature.

Original languageEnglish
Article number033120
JournalChaos
Volume17
Issue number3
DOIs
Publication statusPublished - 2007

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Physics and Astronomy(all)
  • Applied Mathematics

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