Efficient determination of the hyperparameter in regularized total least squares problems

被引：10
|
作者：
Lampe, J. [1 ]
Voss, H. [1 ]
机构：
[1] Hamburg Univ Technol, Inst Numer Simulat, D-21071 Hamburg, Germany
来源：
APPLIED NUMERICAL MATHEMATICS | 2012年 / 62卷 / 09期
关键词：
Total least squares; Regularization; Ill-posedness; Nonlinear Arnoldi method; L-curve; TIKHONOV REGULARIZATION; ARNOLDI METHOD; L-CURVE; ALGORITHM;
D O I：
10.1016/j.apnum.2010.06.005
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The total least squares (TLS) method is a successful approach for linear problems if both the system matrix and the right-hand side are contaminated by some noise. For ill-posed TLS problems regularization is necessary to stabilize the computed solution. In this paper we suggest the use of the L-curve for the determination of the regularization parameter. The focus is on efficient implementation with particular emphasis on the reuse of information gained during the convergence history. (c) 2010 IMACS. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码：1229 / 1241
页数：13
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