Journal of Nonlinear Mathematical Physics

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
Available Online 1 March 2009.
DOI
https://doi.org/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.
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Journal
Journal of Nonlinear Mathematical Physics
Volume-Issue
2 - 1
Pages
1 - 9
Publication Date
2009/03
ISSN (Online)
1776-0852
ISSN (Print)
1402-9251
DOI
https://doi.org/10.2991/jnmp.2009.2.1.1How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Yonggang Chen
AU  - Yunrui Guo
AU  - Wenlin Li
PY  - 2009
DA  - 2009/03
TI  - Novel Robust Stability Criteria for Uncertain Stochastic Neural Networks with Time-Varying Delay
JO  - Journal of Nonlinear Mathematical Physics
SP  - 1
EP  - 9
VL  - 2
IS  - 1
SN  - 1776-0852
UR  - https://doi.org/10.2991/jnmp.2009.2.1.1
DO  - https://doi.org/10.2991/jnmp.2009.2.1.1
ID  - Chen2009
ER  -