Global asymptotic stability analysis for cellular neural networks with time delays
Junwei Lu,
Yiqian Guo and
Shengyuan Xu
Chaos, Solitons & Fractals, 2006, vol. 29, issue 2, 349-353
Abstract:
This paper provides a new sufficient condition for the global asymptotic stability and uniqueness of the equilibrium point of cellular neural networks with time delays. This condition is expressed in terms of linear matrix inequalities, which can be easily checked by various recently developed algorithms in solving convex optimization problems. Numerical examples are provided to show that the proposed stability result is less conservative than some previously established ones in the literature.
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (28)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077905006600
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:29:y:2006:i:2:p:349-353
DOI: 10.1016/j.chaos.2005.08.046
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. ().