SEMI-CONVERGENCE AND RELAXATION PARAMETERS FOR A CLASS OF SIRT ALGORITHMS

被引：0

作者：

Elfving, Tommy ^{[1
]}

Nikazad, Touraj ^{[2
]}

Hansen, Per Christian ^{[3
]}

机构：

[1] Linkoping Univ, Dept Math, SE-58183 Linkoping, Sweden

[2] Iran Univ Sci & Technol, Dept Math, Tehran 1684613114, Iran

[3] Tech Univ Denmark, Dept Informat & Math Modelling, DK-2800 Lyngby, Denmark

来源：

ELECTRONIC TRANSACTIONS ON NUMERICAL ANALYSIS | 2010年 / 37卷

关键词：

SIRT methods; Cimmino and DROP iteration; semi-convergence; relaxation parameters; tomographic imaging; ITERATIVE ALGORITHMS; ACCELERATION; PROJECTIONS;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper is concerned with the Simultaneous Iterative Reconstruction Technique (SIRT) class of iterative methods for solving inverse problems. Based on a careful analysis of the semi-convergence behavior of these methods, we propose two new techniques to specify the relaxation parameters adaptively during the iterations, so as to control the propagated noise component of the error. The advantage of using this strategy for the choice of relaxation parameters on noisy and ill-conditioned problems is demonstrated with an example from tomography (image reconstruction from projections).

引用

页码：321 / 336

页数：16

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