Robust Mean Square Exponential Stability of Stochastic Interval Cellular Neural Networks with Time-delays
- 10.2991/icacsei.2013.69How to use a DOI?
- Robust Mean Square, Neural Networks, Time-delays.
The problem of robust mean-square exponential stability for a class of stochastic interval cellular neural networks with time-delays is investigated. Firstly, a kind of equivalent description of this stochastic interval delayed cellular neural networks is presented. Then by using the formula, Razumikhin theorems, Lyapunov function and norm inequalities, several simple sufficient conditions are obtained which guarantee the robust mean-square exponential stability of the stochastic interval cellular neural networks. and some recent results reported in the literatures are generalized.
- © 2013, 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/).
Cite this article
TY - CONF AU - Zhi chao Liu AU - Jin fang Han PY - 2013/08 DA - 2013/08 TI - Robust Mean Square Exponential Stability of Stochastic Interval Cellular Neural Networks with Time-delays BT - Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013) PB - Atlantis Press SP - 276 EP - 280 SN - 1951-6851 UR - https://doi.org/10.2991/icacsei.2013.69 DO - 10.2991/icacsei.2013.69 ID - Liu2013/08 ER -