Global robust exponential stability analysis for interval neural networks with time-varying delays
Chuandong Li,
Xiaofeng Liao,
Rong Zhang and
Ashutosh Prasad
Chaos, Solitons & Fractals, 2005, vol. 25, issue 3, 751-757
Abstract:
The problem of the global robust exponential stability of interval neural networks with the time-varying delays is investigated. New stability criteria for such problem are derived by an approach combining the Lyapunov–Krasovskii functional with the linear matrix inequality. The effectiveness of the present results is demonstrated by two numerical examples.
Date: 2005
References: View complete reference list from CitEc
Citations: View citations in EconPapers (30)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077904007787
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:25:y:2005:i:3:p:751-757
DOI: 10.1016/j.chaos.2004.11.053
Access Statistics for this article
Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros
More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().