Large-scale Tikhonov regularization via reduction by orthogonal projection

被引：43

作者：

Lampe, Joerg ^{[1
]}

Reichel, Lothar ^{[2
]}

Voss, Heinrich ^{[1
]}

机构：

[1] Hamburg Univ Technol, Inst Numer Simulat, D-21071 Hamburg, Germany

[2] Kent State Univ, Dept Math Sci, Kent, OH 44242 USA

来源：

LINEAR ALGEBRA AND ITS APPLICATIONS | 2012年 / 436卷 / 08期

关键词：

Least squares; General-form Tikhonov regularization; Discrepancy principle; Ill-posedness; L-CURVE; ALGORITHM;

D O I：

10.1016/j.laa.2011.07.019

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper presents a new approach to computing an approximate solution of Tikhonov-regularized large-scale ill-posed least-squares problems with a general regularization matrix. The iterative method applies a sequence of projections onto generalized Krylov subspaces. A suitable value of the regularization parameter is determined by the discrepancy principle. (C) 2011 Elsevier Inc. All rights reserved.

引用

页码：2845 / 2865

页数：21

共 28 条

[1] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].