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Global asymptotic stability analysis for neutral stochastic neural networks with time-varying delays

✍ Scribed by Weiwei Su; Yiming Chen

Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
184 KB
Volume
14
Category
Article
ISSN
1007-5704

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✦ Synopsis

In this paper, the global asymptotic stability is investigated for a class of neutral stochastic neural networks with time-varying delays and norm-bounded uncertainties. Based on Lyapunov stability theory and stochastic analysis approaches, delay-dependent criteria are derived to ensure the global, robust, asymptotic stability of the addressed system in the mean square for all admissible parameter uncertainties. The criteria can be checked easily by the LMI Control Toolbox in Matlab. A numerical example is given to illustrate the feasibility and effectiveness of the results.

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