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We consider perturbed nonlinear ill-posed equations in Hilbert spaces, with operators that are monotone on a given closed convex subset. A simple stable approach is Lavrentiev regularization, but existence of solutions of the regularized…

Numerical Analysis · Mathematics 2018-06-05 Robert Plato , Bernd Hofmann

In the literature on singular perturbation (Lavrentiev regularization) for the stable approximate solution of operator equations with monotone operators in the Hilbert space the phenomena of conditional stability and local well-posedness…

Numerical Analysis · Mathematics 2016-11-23 Radu Ioan Bot , Bernd Hofmann

This paper addresses Tikhonov like regularization methods with convex penalty functionals for solving nonlinear ill-posed operator equations formulated in Banach or, more general, topological spaces. We present an approach for proving…

Numerical Analysis · Mathematics 2009-06-19 Jens Geissler , Bernd Hofmann

We introduce subgradient-based Lavrentiev regularisation of the form \begin{equation*} \mathcal{A}(u) + \alpha \partial \mathcal{R}(u) \ni f^\delta \end{equation*} for linear and nonlinear ill-posed problems with monotone operators…

Optimization and Control · Mathematics 2024-10-01 Markus Grasmair , Fredrik Hildrum

In this paper, we prove optimal convergence rates results for regularisation methods for solving linear ill-posed operator equations in Hilbert spaces. The result generalises existing convergence rates results on optimality to general…

Functional Analysis · Mathematics 2015-11-11 Vinicius Albani , Peter Elbau , Maarten V. de Hoop , Otmar Scherzer

In recent years, a series of convergence rates conditions for regularization methods has been developed. Mainly, the motivations for developing novel conditions came from the desire to carry over convergence rates results from the Hilbert…

Functional Analysis · Mathematics 2014-09-29 Roman Andreev , Peter Elbau , Maarten V. de Hoop , Lingyun Qiu , Otmar Scherzer

This paper provides a new regularization method which is particularly suitable for linear exponentially ill-posed problems. Under logarithmic source conditions (which have a natural interpretation in terms of Sobolev spaces in the…

Numerical Analysis · Mathematics 2020-07-08 Walter Cedric Simo Tao Lee

In this paper, we apply a new kind of smoothness concept, i.e. H\"older stability estimates for the determination of convergence rates of Tikhonov regularization for linear and non-linear inverse problems in Hilbert spaces. For linear…

Numerical Analysis · Mathematics 2020-11-05 Gaurav Mittal , Ankik Kumar Giri

This paper deals with Lavrentiev regularization for solving linear ill-posed problems, mostly with respect to accretive operators on Hilbert spaces. We present converse and saturation results which are an important part in regularization…

Numerical Analysis · Mathematics 2016-07-19 Robert Plato

We study the application of Tikhonov regularization to ill-posed nonlinear operator equations. The objective of this work is to prove low order convergence rates for the discrepancy principle under low order source conditions of logarithmic…

Numerical Analysis · Mathematics 2023-05-02 Chantal Klinkhammer , Robert Plato

Variational source conditions proved useful for deriving convergence rates for Tikhonov's regularization method and also for other methods. Up to now such conditions have been verified only for few examples or for situations which can be…

Numerical Analysis · Mathematics 2017-09-19 Jens Flemming

We consider hierarchical variational inequality problems, or more generally, variational inequalities defined over the set of zeros of a monotone operator. This framework includes convex optimization over equilibrium constraints and…

Optimization and Control · Mathematics 2026-01-07 Daniel Cortild , Meggie Marschner , Mathias Staudigl

These lecture notes for a graduate class present the regularization theory for linear and nonlinear ill-posed operator equations in Hilbert spaces. Covered are the general framework of regularization methods and their analysis via spectral…

Functional Analysis · Mathematics 2021-02-09 Christian Clason

In this paper we investigate the problem of identifying the source term in an elliptic system from a single noisy measurement couple of the Neumann and Dirichlet data. A variational method of Tikhonov-type regularization with specific…

Analysis of PDEs · Mathematics 2019-03-15 Michael Hinze , Bernd Hofmann , Tran Nhan Tam Quyen

In this paper we consider convex Tikhonov regularisation for the solution of linear operator equations on Hilbert spaces. We show that standard fractional source conditions can be employed in order to derive convergence rates in terms of…

Optimization and Control · Mathematics 2020-02-24 Markus Grasmair

Convergence rates results for Tikhonov regularization of nonlinear ill-posed operator equations in abstract function spaces require the handling of both smoothness conditions imposed on the solution and structural conditions expressing the…

Numerical Analysis · Mathematics 2009-09-29 Radu Ioan Bot , Bernd Hofmann

For the Tikhonov regularization of ill-posed nonlinear operator equations, convergence is studied in a Hilbert scale setting. We include the case of oversmoothing penalty terms, which means that the exact solution does not belong to the…

Numerical Analysis · Mathematics 2020-02-03 Bernd Hofmann , Robert Plato

We propose and analyze variational source conditions (VSC) for the Tikhonov regularization method with Lp-norm penalties for a general ill-posed operator equation in a Banach space. Our analysis is based on the use of the celebrated…

Functional Analysis · Mathematics 2021-02-22 De-Han Chen , Irwin Yousept

In this paper, we consider the nonlinear ill-posed inverse problem with noisy data in the statistical learning setting. The Tikhonov regularization scheme in Hilbert scales is considered to reconstruct the estimator from the random noisy…

Statistics Theory · Mathematics 2024-04-09 Abhishake Rastogi

In this paper, we study the Tikhonov regularization scheme in Hilbert scales for the nonlinear statistical inverse problem with a general noise. The regularizing norm in this scheme is stronger than the norm in Hilbert space. We focus on…

Statistics Theory · Mathematics 2024-04-09 Abhishake Rastogi
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