Title :
LMI approach for stability in stochastic delayed neural systems
Author :
Xuyang Lou ; Yong Qiao ; Cui, B.T. ; Ye, Q.
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
Abstract :
In this paper, the asymptotic stability analysis problem is considered for a class of stochastic Cohen-Grossberg neural networks with time-varying delays. We aim to construct easily verifiable conditions for the asymptotic stability in the mean square of the delayed neural networks. Via a Lyapunov functional and the Halanay inequality technique, several stability criteria are derived. Two examples are provided to illustrate the effectiveness and applicability of the proposed criteria.
Keywords :
Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; Halanay inequality technique; LMI approach; Lyapunov functional; asymptotic stability analysis problem; linear matrix inequality; mean square; stability criteria; stochastic Cohen-Grossberg neural networks; stochastic delayed neural systems; time-varying delays; Asymptotic stability; Delays; Neural networks; Stability criteria; Stochastic processes; Symmetric matrices; Halanay inequality; Linear matrix inequality; Lyapunov functional; Neural networks;
Conference_Titel :
Natural Computation (ICNC), 2014 10th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5150-5
DOI :
10.1109/ICNC.2014.6975809
