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- W2077260859 abstract "Many iterative methods that are used to solve Ax=b can be derived as quasi-Newton methods for minimizing the quadratic function 1/2 x<sup>T</sup>A<sup>T</sup>Ax-x<sup>T</sup>A<sup>T</sup>b. In this paper, several such methods are considered, including conjugate gradient least squares (CGLS), Barzilai-Borwein (BB), residual norm steepest descent (RNSD) and Landweber (LW). Regularization properties of these methods are studied by analyzing the so-called filter factors. The algorithm proposed by Barzilai and Borwein is shown to have very favorable regularization and convergence properties. Secondly, we find that preconditioning can result in much better convergence properties for these iterative methods." @default.
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- W2077260859 date "2004-10-26" @default.
- W2077260859 modified "2023-09-23" @default.
- W2077260859 title "Quasi-Newton methods for image restoration" @default.
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- W2077260859 doi "https://doi.org/10.1117/12.561060" @default.
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