The balancing principle in solving semi-discrete inverse problems in Sobolev scales by Tikhonov method

DOI10.1080/00036811.2010.538684zbMath1254.47012OpenAlexW2068015811WikidataQ58160190 ScholiaQ58160190MaRDI QIDQ2883290

Evgeniy A. Volynets, Sergei G. Solodky, Sergei V. Pereverzyev

Publication date: 11 May 2012

Published in: Applicable Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00036811.2010.538684

zbMATH Keywords

collocation methoderror boundTikhonov regularizationa posteriori parameter choiceinverse problems in Sobolev scales

Mathematics Subject Classification ID

Hilbert spaces with reproducing kernels (= (proper) functional Hilbert spaces, including de Branges-Rovnyak and other structured spaces) (46E22) Linear operators and ill-posed problems, regularization (47A52) Linear integral equations (45A05) Inverse problems for integral equations (45Q05)

Related Items (2)

Regularized Quadrature Methods for Fredholm Integral Equations of the First Kind ⋮ Multiscale support vector approach for solving ill-posed problems

Cites Work

• On the regularization of projection methods for solving ill-posed problems
• Optimal Discretization of Inverse Problems in Hilbert Scales. Regularization and Self-Regularization of Projection Methods
• Regularization of some linear ill-posed problems with discretized random noisy data
• An a Posteriori Parameter Choice for Tikhonov Regularization in Hilbert Scales Leading to Optimal Convergence Rates
• Sobolev error estimates and a priori parameter selection for semi-discrete Tikhonov regularization
• How general are general source conditions?
• On the Adaptive Selection of the Parameter in Regularization of Ill-Posed Problems

This page was built for publication: The balancing principle in solving semi-discrete inverse problems in Sobolev scales by Tikhonov method