Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
410457 | Neurocomputing | 2009 | 8 Pages |
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.
Related Topics
Physical Sciences and Engineering
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Authors
P. Balasubramaniam, S. Lakshmanan, R. Rakkiyappan,