Delay-Dependent Filtering of Markovian Jumping Neural Networks With Mode-Dependent Time Delays

被引:0
|
作者
Huang, He [1 ]
Chen, Xiaoping [1 ]
Hua, Qiang [1 ]
机构
[1] Soochow Univ, Sch Elect & Informat Engn, Suzhou 215006, Peoples R China
基金
中国国家自然科学基金;
关键词
Markovian Jumping Neural Networks; Time Delays; Filtering; Convex Optimization; ROBUST STATE ESTIMATION; EXPONENTIAL STABILITY; H-INFINITY; DISCRETE;
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
This paper is concerned with the problem of delay-dependent L-2 - L-infinity filter design of Markovian jumping neural networks with mode-dependent time delays. By constructing a suitable stochastic Lyapunov functional, a delay-dependent condition is established such that the filtering error system is stochastically stable and a prescribed L-2 - L-infinity performance is achieved. Furthermore, it is shown that the gain matrices and the optimal L-2 - L-infinity performance index are obtained by solving a convex optimization problem subject to some linear matrix inequalities. An example is finally provided to demonstrate the effectiveness of the developed result,
引用
收藏
页码:3348 / 3353
页数:6
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