Generalized rank-constrained matrix approximations

被引：61

作者：

Friedland, Shmuel ^{[1
]}

Torokhti, Anatoli

机构：

[1] Univ Illinois, Dept Math Stat & Comp Sci, Chicago, IL 60607 USA

[2] Univ S Australia, Sch Math & Stat, Mawson Lakes, SA 5095, Australia

来源：

SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS | 2007年 / 29卷 / 02期

关键词：

singular value decomposition (SVD); generalized rank-constrained matrix approximations; generalized inverse;

D O I：

10.1137/06065551

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper we give an explicit solution to the rank-constrained matrix approximation in Frobenius norm, which is a generalization of the classical approximation of an m x n matrix A by a matrix of, at most, rank k.

引用

页码：656 / 659

页数：4

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