Boundedness and exponential stability for nonautonomous cellular neural networks with reaction–diffusion terms
Xuyang Lou and
Baotong Cui
Chaos, Solitons & Fractals, 2007, vol. 33, issue 2, 653-662
Abstract:
Employing Lyapunov functional method, we analyze the ultimate boundedness and global exponential stability of a class of reaction–diffusion cellular neural networks with time-varying delays. Some new criteria are obtained to ensure ultimate boundedness and global exponential stability of delayed reaction–diffusion cellular neural networks (DRCNNs). Without assuming that the activation functions fijl(·) are bounded, the results extend and improve the earlier publications.
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077906000890
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:33:y:2007:i:2:p:653-662
DOI: 10.1016/j.chaos.2006.01.044
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. ().