An optimal regularized projection method for solving ill-posed problems via dynamical systems method

DOI10.1016/J.JMAA.2010.05.023zbMath1201.65097OpenAlexW2092443182MaRDI QIDQ984793

Xingjun Luo, Fanchun Li

Publication date: 20 July 2010

Published in: Journal of Mathematical Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmaa.2010.05.023

zbMATH Keywords

computational complexityHilbert spaceprojection methoddiscrepancy principleregularization methodlinear ill-posed problembounded linear operatorminimum norm solutionabstract Cauchy problemsdynamical systems methodasymptotic regularizationparameter choice strategy

Mathematics Subject Classification ID

Numerical methods for initial value problems involving ordinary differential equations (65L05) Numerical solutions to equations with linear operators (65J10) Linear differential equations in abstract spaces (34G10) Complexity and performance of numerical algorithms (65Y20) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Linear operators and ill-posed problems, regularization (47A52)

Related Items (1)

A posteriori parameter choice strategy for fast multiscale methods solving ill-posed integral equations

Cites Work

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• On the regularization of projection methods for solving ill-posed problems
• Dynamical systems method for solving operator equations.
• Dynamical systems method for solving linear finite-rank operator equations
• On a quasi-optimal regularized projection method for solving operator equations of the first kind
• On the asymptotic order of accuracy of Tikhonov regularization
• An adaptive discretization for Tikhonov-Phillips regularization with a posteriori parameter selection

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