Convergence results of nonlinear problems based on Tikhonov regularization method

DOI10.1080/00036811.2022.2143354zbMATH Open1540.65166MaRDI QIDQ6549346

Jinping Wang, Author name not available (Why is that?)

Publication date: 3 June 2024

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

Mathematics Subject Classification ID

Numerical solutions to equations with nonlinear operators (65J15) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Linear operators and ill-posed problems, regularization (47A52)

Cites Work

• On the generalized discrepancy principle for Tikhonov regularization in Hilbert scales
• Rate of convergence of stochastic iteration procedures in ill-posed problems
• Finite-dimensional approximation of tikhonov regularized solutions of non-linear ill-posed problems
• The iteratively regularized Gauss–Newton method with convex constraints and applications in 4Pi microscopy
• Convergence rates for regularization of ill-posed problems in Banach spaces by approximate source conditions
• Convergence rates for the iteratively regularized Gauss–Newton method in Banach spaces
• Approximate source conditions for nonlinear ill-posed problems—chances and limitations
• Discretization strategy for linear ill-posed problems in variable Hilbert scales
• A convergence rates result for Tikhonov regularization in Banach spaces with non-smooth operators
• A discrete scheme of Landweber iteration for solving nonlinear ill-posed problems

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