Delay-interval dependent robust stability criteria for stochastic neural networks with linear fractional uncertainties

Authors:
P. Balasubramaniam;S. Lakshmanan;R. Rakkiyappan
Affiliations:
Department of Mathematics, Gandhigram Rural University, Gandhigram - 624 302, Tamilnadu, India;Department of Mathematics, Gandhigram Rural University, Gandhigram - 624 302, Tamilnadu, India;Department of Mathematics, Gandhigram Rural University, Gandhigram - 624 302, Tamilnadu, India
Venue:
Neurocomputing
Year:
2009

Citing 4
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Abstract

In this paper, we study the delay-interval dependent robust stability criteria for stochastic neural networks with linear fractional uncertainties. The time-varying delay is assumed to belong to an interval and is a fast time-varying function. The uncertainty under consideration includes linear fractional norm-bounded uncertainty. Based on the new Lyapunov-Krasovskii functional, some inequality techniques and stochastic stability theory, delay-interval dependent stability criteria are obtained in terms of linear matrix inequalities. Finally, some numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed LMI conditions.