|本期目录/Table of Contents|

[1]柴伟,孙先仿.集员估计的加权最小二乘支持向量机方法[J].电机与控制学报,2009,(03):431-435.
 CHAI Wei,SUN Xian-fang.Set membership estimation by weighted least squares support vector machines[J].,2009,(03):431-435.
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
期数:
2009年03
页码:
431-435
栏目:
出版日期:
2009-05-15

文章信息/Info

Title:
Set membership estimation by weighted least squares support vector machines
作者:
柴伟; 孙先仿
北京航空航天大学自动化科学与电气工程学院; 北京工业大学电子信息与控制工程学院
Author(s):
CHAI Wei; SUN Xian-fang
关键词:
非线性系统 参数估计 集员 支持向量机 加权最小二乘
Keywords:
nonlinear systems parameter estimation set membership support vector machines weighted least squares
分类号:
TP13
DOI:
-
文献标志码:
A
摘要:
针对带有未知但有界误差的参数非线性回归模型,提出了集员估计的加权最小二乘支持向量机方法。采用加权最小二乘支持向量回归的方法建立逼近方程误差向量的加权l∞范数与参数向量之间的复杂函数关系的模型。根据此模型和可行的方程误差向量的加权l∞范数导出近似参数可行集。为了评估集员估计结果的优劣,给出了反映近似边界接近精确边界程度的指标。仿真结果表明,采用本文方法比采用一般最小二乘支持向量机的方法所得的近似边界更接近精确边界。
Abstract:
A set membership estimation method by weighted least squares support vector machines(LS-SVM) was proposed for nonlinear-in-parameter regression models with unknown but bounded errors.A weighted least squares support vector regression(LS-SVR) was solved to build a model which approximated the complex functional relationship between the weighted l∞ norms of the equation-error vectors and the given parameter vectors.Then the approximate feasible parameter set was obtained according to this model and the feasible weighted l∞ norms of the equation-error vectors.In order to evaluate the results of the proposed method,an index reflecting the closeness between the approximate boundary and the true boundary was given.The simulation results show that the proposed method can give approximate boundaries much closer to true boundaries than the method by unweighted LS-SVM.

参考文献/References:

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备注/Memo

备注/Memo:
国家自然科学基金(60674030,60234010);; 北京市自然科学基金(4032014)
更新日期/Last Update: 2009-07-09