Sampled-data state estimation for neural networks of neutral type

被引：4
|
作者：
Yang, Changchun [1 ]
Yang, Yongqing [1 ,2 ]
Hu, Manfeng [1 ]
Xu, Xianyun [1 ]
机构：
[1] Jiangnan Univ, Sch Sci, Wuxi 214122, Peoples R China
[2] Jiangnan Univ, Minist Educ, Key Lab Adv Proc Control Light Ind, Wuxi 214122, Peoples R China
来源：
ADVANCES IN DIFFERENCE EQUATIONS | 2014年
基金：
中国国家自然科学基金; 中央高校基本科研业务费专项资金资助;
关键词：
neural network; sampled-data; state estimation; neutral type; LMIs; TIME-VARYING DELAYS; LYAPUNOV FUNCTIONAL-APPROACH; STABILITY ANALYSIS; DISCRETE; DESIGN;
D O I：
10.1186/1687-1847-2014-138
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, the sampled-data state estimation is investigated for a class of neural networks of neutral type. By employing a suitable Lyapunov functional, a delay-dependent criterion is established to guarantee the existence of the sampled-data estimator. The estimator gain matrix can be obtained by solving linear matrix inequalities (LMIs). A numerical example is given to show the effectiveness of the proposed method.
引用
收藏
页数：11
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