北京科技大学学报2012，Vol.34Issue(7)：847-852,6.
混合时变时滞神经网络的状态估计器设计
Design of state estimators for neural networks with mixed time-varying delays
摘要
Abstract
The state estimation problem was studied for neural networks with mixed discrete and distributed time-varying delays as well as general activation functions. The discrete time-varying delay varies in an interval, where the lower bound is not fixed to be zero. Defining a novel Lyapunov functional and using the Jensen integral inequality, a delay-interval-dependent criterion is provided to design a state estimator through available output measurements in terms of a linear matrix inequality （ LM1）, such that the error-state system is globally asymptotically stable. A numerical example was given to illustrate that this result is more effective and less conservative than some existing ones.关键词
状态估计/时变网络/时滞/神经网络/线性矩阵不等式（LMI）/Lyapunov函数Key words
state estimation/time-varying networks/delays/neural networks/linear matrix inequalities/Lyapunov functions分类
计算机与自动化引用本文复制引用
张蕾,刘贺平,王健安..混合时变时滞神经网络的状态估计器设计[J].北京科技大学学报,2012,34(7):847-852,6.基金项目
上海海洋大学博士启动基金项目 （）
