Estimating Solution Smoothness and Data Noise with Tikhonov Regularization

DOI10.1080/01630563.2021.2007948zbMath1492.65150arXiv2012.14875OpenAlexW3215324085MaRDI QIDQ5071316

Daniel Gerth, Ronny Ramlau

Publication date: 21 April 2022

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2012.14875

zbMATH Keywords

Tikhonov regularizationill-posed problemsource conditionnoise level estimation

Mathematics Subject Classification ID

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

Cites Work

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• On Converse and Saturation Results for Tikhonov Regularization of Linear Ill-Posed Problems
• The quasi-optimality criterion in the linear functional strategy
• A new interpretation of (Tikhonov) regularization
• Heuristic Parameter Choice Rules for Tikhonov Regularization with Weakly Bounded Noise
• Analysis of regularized inversion of data corrupted by white Gaussian noise

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