Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay

This paper considers the robust stability analysis problem for a class of uncertain stochastic neural net- works with time-varying delay. Based on the Lyapunov functional method, and by resorting to the new technique for estimating the upper bound of the stochastic derivative of Lyapunov functionals...

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Main Authors: Yunrui Guo, Yonggang Chen, Wenlin Li
Format: Article
Language:English
Published: Springer 2009-03-01
Series:International Journal of Computational Intelligence Systems
Online Access:https://www.atlantis-press.com/article/1815.pdf
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author Yunrui Guo
Yonggang Chen
Wenlin Li
author_facet Yunrui Guo
Yonggang Chen
Wenlin Li
author_sort Yunrui Guo
collection DOAJ
description This paper considers the robust stability analysis problem for a class of uncertain stochastic neural net- works with time-varying delay. Based on the Lyapunov functional method, and by resorting to the new technique for estimating the upper bound of the stochastic derivative of Lyapunov functionals, the novel asymptotic stability criteria are obatined in terms of Linear matrix inequalities (LMIs). Two numerical examples are presented to show the effectiveness and the less conservativeness of the proposed method. Keywords: robust stability, stochastic neural networks, time-varying delay, linear matrix inequalities.
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spelling doaj.art-94ede88e42ee4672bb9c2a3704cc1a882022-12-22T02:55:06ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832009-03-012110.2991/jnmp.2009.2.1.1Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying DelayYunrui GuoYonggang ChenWenlin LiThis paper considers the robust stability analysis problem for a class of uncertain stochastic neural net- works with time-varying delay. Based on the Lyapunov functional method, and by resorting to the new technique for estimating the upper bound of the stochastic derivative of Lyapunov functionals, the novel asymptotic stability criteria are obatined in terms of Linear matrix inequalities (LMIs). Two numerical examples are presented to show the effectiveness and the less conservativeness of the proposed method. Keywords: robust stability, stochastic neural networks, time-varying delay, linear matrix inequalities.https://www.atlantis-press.com/article/1815.pdf
spellingShingle Yunrui Guo
Yonggang Chen
Wenlin Li
Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay
International Journal of Computational Intelligence Systems
title Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay
title_full Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay
title_fullStr Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay
title_full_unstemmed Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay
title_short Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay
title_sort novel robust stability criteria for uncertain stochastic neural networks with time varying delay
url https://www.atlantis-press.com/article/1815.pdf
work_keys_str_mv AT yunruiguo novelrobuststabilitycriteriaforuncertainstochasticneuralnetworkswithtimevaryingdelay
AT yonggangchen novelrobuststabilitycriteriaforuncertainstochasticneuralnetworkswithtimevaryingdelay
AT wenlinli novelrobuststabilitycriteriaforuncertainstochasticneuralnetworkswithtimevaryingdelay