Delay-dependent robust stability analysis of uncertain stochastic neural networks with discrete interval and distributed time-varying delays |
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Authors: | P. R. |
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Affiliation: | aDepartment of Mathematics, Gandhigram Rural University, Gandhigram 624 302, Tamilnadu, India |
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Abstract: | This paper is concerned with stability analysis problem for uncertain stochastic neural networks with discrete interval and distributed time-varying delays. The parameter uncertainties are assumed to be norm bounded and the delay 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. Based on the new Lyapunov–Krasovskii functional and stochastic stability theory, delay-interval dependent stability criteria are obtained in terms of linear matrix inequalities. Some numerical examples and comparisons are provided to show that the proposed results significantly improve the allowable upper and lower bounds of delays over some existing results in the literature. Furthermore, the supplementary requirement that the time derivative of discrete time-varying delays must be smaller than the value one is not necessary to derive the results in this paper. |
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Keywords: | Delay/interval dependent stability Linear matrix inequality Lyapunov– Krasovskii functional Stochastic neural networks |
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