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

页码：52 / 60

页数：9

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