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Volume 2, Issue 1, March 2009, Pages 1 - 9
Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay
Authors
Yonggang Chen, Yunrui Guo, Wenlin Li
Corresponding Author
Yonggang Chen
Received 1 February 2008, Revised 28 January 2009, Available Online 1 March 2009.
- DOI
- 10.2991/jnmp.2009.2.1.1How to use a DOI?
- Abstract
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.
- Copyright
- © 2009, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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Cite this article
TY - JOUR AU - Yonggang Chen AU - Yunrui Guo AU - Wenlin Li PY - 2009 DA - 2009/03/01 TI - Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay JO - International Journal of Computational Intelligence Systems SP - 1 EP - 9 VL - 2 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/jnmp.2009.2.1.1 DO - 10.2991/jnmp.2009.2.1.1 ID - Chen2009 ER -