The revisited total least squares problems with linear equality constraint

被引：6

作者：

Liu, Qiaohua ^{[1
]}

Jin, Shufang ^{[1
]}

Yao, Lei ^{[1
]}

Shen, Dongmei ^{[2
]}

机构：

[1] Shanghai Univ, Dept Math, Shanghai 200444, Peoples R China

[2] Shanghai Lixin Univ Accounting & Finance, Sch Stat & Math, Shanghai 201209, Peoples R China

来源：

APPLIED NUMERICAL MATHEMATICS | 2020年 / 152卷

基金：

中国国家自然科学基金;

关键词：

Total least squares; Linear equality constraints; The method of weighting; Weighting factor; Inverse iteration method;

D O I：

10.1016/j.apnum.2019.11.021

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The total least squares problem with linear equality constraint is proved to be approximated by an unconstrained total least squares problem with a large weight on the constraint. A criterion for choosing the weighting factor is given, and a QR-based inverse (QR-INV) iteration method is presented. Numerical results show that the QR-INV method is more efficient than the standard QR-SVD procedure and Schaffrin's inverse iteration method, especially for large and sparse matrices. (C) 2019 IMACS. Published by Elsevier B.V. All rights reserved.

引用

页码：275 / 284

页数：10

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