On robust stability of uncertain stochastic neural networks with distributed and interval time-varying delays

Wei Feng, Simon X. Yang and Haixia Wu

Chaos, Solitons & Fractals, 2009, vol. 42, issue 4, 2095-2104

Abstract: This paper is concerned with the robust asymptotic stability analysis problem for stochastic uncertain neural networks with distributed and interval time-varying delays. By using the stochastic analysis approach, employing some free-weighting matrices and introducing an appropriate type of Lyapunov functional which take into account the ranges of delays, some new delay-range-dependent and rate-dependent stability criteria are established in terms of linear matrix inequalities (LMIs) to guarantee the delayed neural networks to be robustly asymptotically stable in the mean square. And the new criteria are applicable to both fast and slow time-varying delays. Three numerical examples have also been used to demonstrate the usefulness of the main results.

Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077909003099
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:42:y:2009:i:4:p:2095-2104

DOI: 10.1016/j.chaos.2009.03.141

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. ().