State Estimation for Neural Networks with Time-Varying Discrete and Distributed Delays

被引：0

作者：

Zhang Yuejin ^{[1
]}

Zhou Shaosheng ^{[1
]}

Zhang Changxue ^{[2
]}

机构：

[1] Hangzhou Dianzi Univ, Inst Automat, Hangzhou 310018, Peoples R China

[2] Shandong Jianzhu Univ, Sch Sci, Jinan 250101, Shandong, Peoples R China

来源：

PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 6 | 2008年

关键词：

Lyapunov function; Neural networks; Stability; State estimation; Time-varying delays;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the delay-dependent state estimation problem for a class of neural networks with time-varying discrete and distributed delays is concerned. The activation function is assumed to be neither monotonic nor differentiable, and a delay-dependent condition is established in terms of linear matrix inequality (LMI) to guarantee the dynamics of the estimation error is globally asymptotically stable. Finally, a numerical example with simulation results is provided to demonstrate the effectiveness of the proposed design method.

引用

页码：644 / +

页数：2

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