ON ROW RELAXATION METHODS FOR LARGE CONSTRAINED LEAST-SQUARES PROBLEMS

被引：30

作者：

DAX, A

机构：

来源：

SIAM JOURNAL ON SCIENTIFIC COMPUTING | 1993年 / 14卷 / 03期

关键词：

ROW RELAXATION METHODS; LARGE UNSTRUCTURED LEAST SQUARES PROBLEMS; LINEAR CONSTRAINTS; ITERATIVE IMPROVEMENT OF REGULARIZED SOLUTIONS;

D O I：

10.1137/0914036

中图分类号：

O29 [应用数学];

学科分类号：

070104 [应用数学];

摘要：

This paper addresses the question of how to construct a row relaxation method for solving large unstructured linear least squares problems, with or without linear constraints. The proposed approach combines the Herman-Lent-Hurwitz scheme for solving regularized least squares problems with the Lent-Censor-Hildreth method for solving linear constraints. However, numerical experiments show that the Herman-Lent-Hurwitz scheme has difficulty reaching a least squares solution. This difficulty is resolved by applying the Riley-Golub iterative improvement process.

引用

页码：570 / 584

页数：15

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