Subgradient-based Lavrentiev regularisation of monotone ill-posed problems

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Main Authors: Grasmair, Markus, Hildrum, Fredrik
Format: Preprint
Published: 2020
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author Grasmair, Markus
Hildrum, Fredrik
author_facet Grasmair, Markus
Hildrum, Fredrik
contents We introduce subgradient-based Lavrentiev regularisation of the form \begin{equation*} \mathcal{A}(u) + α\partial \mathcal{R}(u) \ni f^δ\end{equation*} for linear and nonlinear ill-posed problems with monotone operators $\mathcal{A}$ and general regularisation functionals $\mathcal{R}$. In contrast to Tikhonov regularisation, this approach perturbs the equation itself and avoids the use of the adjoint of the derivative of $\mathcal{A}$. It is therefore especially suitable for time-causal problems that only depend on information in the past and allows for real-time computation of regularised solutions. We establish a general well-posedness theory in Banach spaces and prove convergence-rate results with variational source conditions. Furthermore, we demonstrate its application in total-variation denoising in linear Volterra integral operators of the first kind and parameter-identification problems in semilinear parabolic PDEs.
format Preprint
id arxiv_https___arxiv_org_abs_2005_08917
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Subgradient-based Lavrentiev regularisation of monotone ill-posed problems
Grasmair, Markus
Hildrum, Fredrik
Optimization and Control
Numerical Analysis
47H05, 47J06, 45Q05, 65J20, 65R30
We introduce subgradient-based Lavrentiev regularisation of the form \begin{equation*} \mathcal{A}(u) + α\partial \mathcal{R}(u) \ni f^δ\end{equation*} for linear and nonlinear ill-posed problems with monotone operators $\mathcal{A}$ and general regularisation functionals $\mathcal{R}$. In contrast to Tikhonov regularisation, this approach perturbs the equation itself and avoids the use of the adjoint of the derivative of $\mathcal{A}$. It is therefore especially suitable for time-causal problems that only depend on information in the past and allows for real-time computation of regularised solutions. We establish a general well-posedness theory in Banach spaces and prove convergence-rate results with variational source conditions. Furthermore, we demonstrate its application in total-variation denoising in linear Volterra integral operators of the first kind and parameter-identification problems in semilinear parabolic PDEs.
title Subgradient-based Lavrentiev regularisation of monotone ill-posed problems
topic Optimization and Control
Numerical Analysis
47H05, 47J06, 45Q05, 65J20, 65R30
url https://arxiv.org/abs/2005.08917