Estimation of the L-curve via Lanczos bidiagonalization

被引:101
作者
Calvetti, D
Golub, GH
Reichel, L
机构
[1] Case Western Reserve Univ, Dept Math, Cleveland, OH 44106 USA
[2] Stanford Univ, Dept Comp Sci, Stanford, CA 94305 USA
[3] Kent State Univ, Dept Math & Comp Sci, Kent, OH 44242 USA
基金
美国国家科学基金会;
关键词
ill-posed problem; regularization; L-curve criterion; Gauss quadrature;
D O I
10.1023/A:1022383005969
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The L-curve criterion is often applied to determine a suitable value of the regularization parameter when solving ill-conditioned linear systems of equations with a right-hand side contaminated by errors of unknown norm. However, the computation of the L-curve is quite costly for large problems; the determination of a point on the L-curve requires that both the norm of the regularized approximate solution and the norm of the corresponding residual vector be available. Therefore, usually only a few points on the L-curve are computed and these values, rather than the L-curve, are used to determine a value of the regularization parameter. We propose a new approach to determine a value of the regularization parameter based on computing an L-ribbon that contains the L-curve in its interior. An L-ribbon can be computed fairly inexpensively by partial Lanczos bidiagonalization of the matrix of the given linear system of equations. A suitable value of the regularization parameter is then determined from the L-ribbon, and we show that an associated approximate solution of the linear system can be computed with little additional work. AMS subject classification: 65J20, 65F30.
引用
收藏
页码:603 / 619
页数:17
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