Robust stability analysis of uncertain stochastic neural networks with interval time-varying delay

Wei Feng, Simon X. Yang, Wei Fu and Haixia Wu

Chaos, Solitons & Fractals, 2009, vol. 41, issue 1, 414-424

Abstract: This paper addresses the stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. The parameter uncertainties are assumed to be norm bounded, and the delay factor is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. A sufficient condition is derived such that for all admissible uncertainties, the considered neural network is robustly, globally, asymptotically stable in the mean square. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI), which can be effectively solved by some standard numerical packages. Finally, numerical examples are provided to demonstrate the usefulness of the proposed criteria.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:41:y:2009:i:1:p:414-424

DOI: 10.1016/j.chaos.2008.01.024

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