Global asymptotic stability of delay BAM neural networks with impulses

Xu Yang Lou and Bao Tong Cui

Chaos, Solitons & Fractals, 2006, vol. 29, issue 4, 1023-1031

Abstract: The global asymptotic stability of delay bi-directional associative memory neural networks with impulses are studied by constructing suitable Lyapunov functional. Sufficient conditions, which are independent to the delayed quantity, are obtained for the global asymptotic stability of the neural networks. Some illustrative examples are given to demonstrate the effectiveness of the obtained results.

Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077905007058
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:4:p:1023-1031

DOI: 10.1016/j.chaos.2005.08.125

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. ().