DocumentCode :
3375682
Title :
Stabilizing of stochastic interval hopfield neural networks with time-varying delays
Author :
Xiaolin Li ; Fuyan Sun
Author_Institution :
Dept. of Mathemaics, Shanghai Univ., Shanghai, China
fYear :
2013
fDate :
16-18 Dec. 2013
Firstpage :
773
Lastpage :
777
Abstract :
In this paper, the stochastic stabilization problem for stochastic interval Hopfield neural networks with time-varying delays is investigated. Our attention is focused on the design of a robust state feedback controller such that the closed-loop system is robustly exponentially stable in the mean square. The sufficient conditions are proposed to ensure the existence of desired robust controller, which can be obtained by solving a linear matrix inequality (LMI). Finally, an example is given to illustrate the effectiveness of our theory results.
Keywords :
Hopfield neural nets; closed loop systems; controllers; linear matrix inequalities; mean square error methods; stochastic processes; time-varying networks; LMI; closed-loop system; linear matrix inequality; mean square; robust state feedback controller; stochastic interval Hopfield neural networks; stochastic stabilization problem; time-varying delays; Biological neural networks; Control theory; Delays; Linear matrix inequalities; Robust stability; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2013 6th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-2760-9
Type :
conf
DOI :
10.1109/BMEI.2013.6747044
Filename :
6747044
Link To Document :
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