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Journal article

Semiconvergence and Relaxation Parameters for Projected SIRT Algorithms

By Elfving, Tommy1; Hansen, Per Christian2,3; Nikazad, Touraj4

From

Linköping University1

Department of Informatics and Mathematical Modeling, Technical University of Denmark2

Scientific Computing, Department of Informatics and Mathematical Modeling, Technical University of Denmark3

Iran University of Science and Technology4

We give a detailed study of the semiconverg ence behavior of projected nonstationary simultaneous iterative reconstruction technique (SIRT) algorithms, including the projected Landweber algorithm. We also consider the use of a relaxation parameter strategy, proposed recently for the standard algorithms, for controlling the semiconvergence of the projected algorithms.

We demonstrate the semiconvergence and the performance of our strategies by examples taken from tomographic imaging. © 2012 Society for Industrial and Applied Mathematics.

Language: English
Publisher: Society for Industrial and Applied Mathematics
Year: 2012
Pages: A2000-A2017
ISSN: 10957197 and 10648275
Types: Journal article
DOI: 10.1137/110834640
ORCIDs: Hansen, Per Christian
Keywords

Algorithms Iterative methods Nonnegativity constraints Parameter estimation Projected Landweber iteration Relaxation parameters Semiconvergence Simultaneous iterative reconstruction technique Tomographic imaging Tomography

Other keywords

65F10 65R32 nonnegativity constraints projected Landweber iteration relaxation parameters semiconvergence simultaneous iterative reconstruction technique tomographic imaging

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