An Algorithm for the Regularization of Ill-Conditioned, Banded Least Squares Problems-Reference-Cited by-同舟云学术

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An Algorithm for the Regularization of Ill-Conditioned, Banded Least Squares Problems

Published:1984-03 Issue:1 Volume:5 Page:237-254
ISSN:0196-5204
Container-title:SIAM Journal on Scientific and Statistical Computing
language:en
Short-container-title:SIAM J. Sci. and Stat. Comput.

Author:

Eldén Lars

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Link

http://epubs.siam.org/doi/pdf/10.1137/0905017

Reference17 articles.

1. Restoration of images degraded by spatially varying pointspread functions by a conjugate gradient method

2. Solving linear least squares problems by Gram-Schmidt orthogonalization

3. Smoothing noisy data with spline functions

4. Review of Fredholm Equations of the First Kind

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1. Regularizing properties of a class of matrices including the optimal and the superoptimal preconditioners;Numerical Linear Algebra with Applications;2018-12-17

2. Operator-theoretic and regularization approaches to ill-posed problems;GEM - International Journal on Geomathematics;2017-12-05

3. Fast Computation of Spectral Projectors of Banded Matrices;SIAM Journal on Matrix Analysis and Applications;2017-01

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