Global robust exponential stability of delayed neural networks: An LMI approach

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Chaos, Solitons & Fractals, 2007, vol. 32, issue 5, 1742-1748

Abstract: In this paper, the problems of determining the robust exponential stability and estimating the exponential convergence rate for neural networks with parametric uncertainties and time delay are studied. Based on Lyapunov–Krasovskii stability theory for functional differential equations and the linear matrix inequality (LMI) technique, some delay-dependent criteria are derived to guarantee global robust exponential stability. The exponential convergence rate can be easily estimated via these criteria.

Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:32:y:2007:i:5:p:1742-1748

DOI: 10.1016/j.chaos.2005.12.026

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