A novel neurocomputing approach to nonlinear stochastic state estimation

被引：0
|
作者：
Menhaj, MB [1 ]
Salmasi, FR [1 ]
机构：
[1] Amirkabir Univ Technol, Dept Elect Engn, Tehran 15914, Iran
来源：
COMPUTATIONAL INTELLIGENCE: THEORY AND APPLICATIONS | 1997年 / 1226卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a novel neuro-computing approach to the problem of state estimation by means of an hybrid combination of Hopfield neural network whose capability of solving certain optimization problems is well-known and feedforward multilayer neural net which is very popular because of its universal approximation property. This neuro-estimator is very appropriate for the real-time implementation of linear or/and especially nonlinear state estimators. Simulation results shows the effectiveness of the proposed method.
引用
收藏
页码：52 / 60
页数：9
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