Sampled-data state estimation for neural networks of neutral type

Advances in Difference Equations

Manfeng Hu¹  Yongqing Yang²  Xianyun Xu²  Changchun Yang² 

[1] Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China;School of Science, Jiangnan University, Wuxi, China

关键词: neural network;    sampled-data;    state estimation;    neutral type;    LMIs;   

DOI  :  10.1186/1687-1847-2014-138

学科分类：数学（综合）

来源: SpringerOpen

【 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.

【 授权许可】

CC BY