Robust Mean Square Exponential Stability of Stochastic Interval Cellular Neural Networks with Time-delays

DOI

10.2991/icacsei.2013.69How to use a DOI?

Keywords

Robust Mean Square, Neural Networks, Time-delays.

Abstract

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.

Copyright

© 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/).

Download article (PDF)

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  -