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In this paper we discuss a deterministic form of ensemble Kalman inversion as a regularization method for linear inverse problems. By interpreting ensemble Kalman inversion as a low-rank approximation of Tikhonov regularization, we are able…

Numerical Analysis · Mathematics 2023-10-31 Fabian Parzer , Otmar Scherzer

Regularization methods are a key tool in the solution of inverse problems. They are used to introduce prior knowledge and make the approximation of ill-posed (pseudo-)inverses feasible. In the last two decades interest has shifted from…

Numerical Analysis · Mathematics 2018-01-31 Martin Benning , Martin Burger

Regularization techniques for the numerical solution of inverse scattering problems in two space dimensions are discussed. Assuming that the boundary of a scatterer is its most prominent feature, we exploit as model the class of…

Functional Analysis · Mathematics 2016-05-05 Gitta Kutyniok , Volker Mehrmann , Philipp Petersen

We consider abstract operator equations $Fu=y$, where $F$ is a compact linear operator between Hilbert spaces $U$ and $V$, which are function spaces on \emph{closed, finite dimensional Riemannian manifolds}, respectively. This setting is of…

Numerical Analysis · Mathematics 2015-05-28 Nicolas Thorstensen , Otmar Scherzer

In this paper we discuss the adjoint stabilised finite element method introduced in, E. Burman, Stabilized finite element methods for nonsymmetric, noncoercive and ill-posed problems. Part I: elliptic equations, SIAM Journal on Scientific…

Numerical Analysis · Mathematics 2015-12-10 Erik Burman

In this paper, we establish an initial theory regarding the Second Order Asymptotical Regularization (SOAR) method for the stable approximate solution of ill-posed linear operator equations in Hilbert spaces, which are models for linear…

Numerical Analysis · Mathematics 2018-08-28 Ye Zhang , Bernd Hofmann

We investigate iterated Tikhonov methods coupled with a Kaczmarz strategy for obtaining stable solutions of nonlinear systems of ill-posed operator equations. We show that the proposed method is a convergent regularization method. In the…

Numerical Analysis · Mathematics 2020-12-23 J. Baumeister , A. De Cezaro , A. Leitao

We design an abstract setting for the approximation in Banach spaces of operators acting in duality. A typical example are the gradient and divergence operators in Lebesgue--Sobolev spaces on a bounded domain. We apply this abstract setting…

Numerical Analysis · Mathematics 2018-06-28 Jérôme Droniou , Robert Eymard , T. Gallouët , R. Herbin

In this paper we study the inverse Laplace transform. We first derive a new global logarithmic stability estimate that shows that the inversion is severely ill-posed. Then we propose a regularization method to compute the inverse Laplace…

Analysis of PDEs · Mathematics 2023-04-18 Pierre Maréchal , Faouzi Triki , Walter C. Simo Tao Lee

In this paper, we consider a modified Levenberg--Marquardt method for solving an ill-posed inverse problem where the forward mapping is not G\^ateaux differentiable. By relaxing the standard assumptions for the classical smooth setting, we…

Numerical Analysis · Mathematics 2019-09-10 Christian Clason , Vu Huu Nhu

The motive of this paper is to discuss the local convergence of a two-step Newton type method of convergence rate three for solving nonlinear equations in Banach spaces. It is assumed that the first order derivative of nonlinear operator…

Numerical Analysis · Mathematics 2021-01-06 Akanksha Saxena , J. P. Jaiswal

Tikhonov regularization is one of the most commonly used methods of regularization of ill-posed problems. In the setting of finite element solutions of elliptic partial differential control problems, Tikhonov regularization amounts to…

Numerical Analysis · Mathematics 2016-09-19 Erik Burman , Peter Hansbo , Mats Larson

We study the solutions of infinite dimensional linear inverse problems over Banach spaces. The regularizer is defined as the total variation of a linear mapping of the function to recover, while the data fitting term is a near arbitrary…

Optimization and Control · Mathematics 2017-11-03 Axel Flinth , Pierre Weiss

We consider the inverse problem of reconstructing the interior boundary curve of a doubly connected domain from the knowledge of the temperature and the thermal flux on the exterior boundary curve. The use of the Laguerre transform in time…

Numerical Analysis · Mathematics 2024-02-23 Roman Chapko , Leonidas Mindrinos

We investigate Tikhonov regularization methods for nonlinear ill-posed problems in Banach spaces, where the penalty term is described by Bregman distances. We prove convergence and stability results. Moreover, using appropriate source…

Numerical Analysis · Mathematics 2020-12-22 I. R. Bleyer , A. Leitao

Considering the question: how non-linear may a non-linear operator be in order to extend the linear regularization theory, we introduce the class of dilinear mappings, which covers linear, bilinear, and quadratic operators between Banach…

Numerical Analysis · Mathematics 2021-03-19 Robert Beinert , Kristian Bredies

We introduce and analyze a fast iterative method based on sequential Bregman projections for nonlinear inverse problems in Banach spaces. The key idea, in contrast to the standard Landweber method, is to use multiple search directions per…

Numerical Analysis · Mathematics 2018-08-01 Anne Wald

We study an abstract linear operator equation on a Banach space by using the inverse of the sum of two sectorial operators. We prove that the boundedness of a special type of operator valued $H^\infty$-calculus is sufficient for maximal…

Functional Analysis · Mathematics 2024-03-22 Nikolaos Roidos

Developments in numerical methods for problems governed by nonlinear partial differential equations underpin simulations with sound arguments in diverse areas of science and engineering. In this paper, we explore the regularization method…

Analysis of PDEs · Mathematics 2020-09-29 Vo Anh Khoa , Mai Thanh Nhat Truong , Nguyen Ho Minh Duy , Nguyen Huy Tuan

In this paper we consider the iteratively regularized Gauss-Newton method, where regularization is achieved by Ivanov regularization, i.e., by imposing a priori constraints on the solution. We propose an a posteriori choice of the…

Numerical Analysis · Mathematics 2019-10-07 Barbara Kaltenbacher , Andrej Klassen , Mario Luiz Previatti de Souza