Large-scale Tikhonov regularization via reduction by orthogonal projection

被引：42
|
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
收藏
页码：2845 / 2865
页数：21
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