An Improved Delay-Dependent Globally Asymptotically Stability Criterion for the Static Neural Networks with Time-Varying Delay
Kai Mao, Bao Shi, Shudong Zhang
Available Online August 2015.
- https://doi.org/10.2991/msam-15.2015.33How to use a DOI?
- static neural networks; lyapunov-krasovskii functional; delay fractioning method; convex combination method; LMIs
- The globally asymptotic stability for static neural networks with time-varying delay is concerned in this paper. By delay fractioning technique and taking more delayed-state variables into account, a newly Lyapunov-Krasovskii Functional was constructed, together with the Jessen integral inequality and convex combination method , a delay-dependent global stability criterion is obtained, it is less conservative than some existing ones. Example is provided to show the effectiveness and reduced conservatism of the proposed results.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Kai Mao AU - Bao Shi AU - Shudong Zhang PY - 2015/08 DA - 2015/08 TI - An Improved Delay-Dependent Globally Asymptotically Stability Criterion for the Static Neural Networks with Time-Varying Delay BT - 2015 International Conference on Modeling, Simulation and Applied Mathematics PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/msam-15.2015.33 DO - https://doi.org/10.2991/msam-15.2015.33 ID - Mao2015/08 ER -