English
Related papers

Related papers: Extrapolated regularization of nearly singular int…

200 papers

We consider a class of difference-of-convex (DC) optimization problems whose objective is level-bounded and is the sum of a smooth convex function with Lipschitz gradient, a proper closed convex function and a continuous concave function.…

Optimization and Control · Mathematics 2017-06-23 Bo Wen , Xiaojun Chen , Ting Kei Pong

A Nystrom-based high-order (HO) discretization scheme for surface integral equations (SIEs) for analyzing the electroencephalography (EEG) forward problem is proposed in this work. We use HO surface elements and interpolation functions for…

Numerical Analysis · Mathematics 2025-12-05 Rui Chen , Viviana Giunzioni , Adrien Merlini , Francesco P. Andriulli

We consider the multidimensional space-fractional diffusion equations with spatially varying diffusivity and fractional order. Significant computational challenges are encountered when solving these equations due both to the kernel…

Numerical Analysis · Mathematics 2021-08-31 Hasnaa Alzahrani , George Turkiyyah , Omar Knio , David Keyes

In this paper we present a general extrapolated elliptic regularity result for second order differential operators in divergence form on fractional Sobolev-type spaces of negative order $X^{s-1,q}_D(\Omega)$ for $s > 0$ small, including…

Analysis of PDEs · Mathematics 2020-03-26 Hannes Meinlschmidt , Joachim Rehberg

We consider filtered subspace iteration for approximating a cluster of eigenvalues (and its associated eigenspace) of a (possibly unbounded) selfadjoint operator in a Hilbert space. The algorithm is motivated by a quadrature approximation…

Numerical Analysis · Mathematics 2019-02-05 Jay Gopalakrishnan , Luka Grubišić , Jeffrey Ovall

In this article we consider regularizations of the Dirac delta distribution with applications to prototypical elliptic and hyperbolic partial differential equations (PDEs). We study the convergence of a sequence of distributions…

Numerical Analysis · Mathematics 2016-11-01 Bamdad Hosseini , Nilima Nigam , John M. Stockie

This work deals with a regularization method enforcing solution sparsity of linear ill-posed problems by appropriate discretization in the image space. Namely, we formulate the so called least error method in an $\ell^1$ setting and perform…

Numerical Analysis · Mathematics 2016-08-03 Kristian Bredies , Barbara Kaltenbacher , Elena Resmerita

Regularization plays an important role in solving ill-posed problems by adding extra information about the desired solution, such as sparsity. Many regularization terms usually involve some vector norm, e.g., $L_1$ and $L_2$ norms. In this…

Numerical Analysis · Mathematics 2021-03-10 Weihong Guo , Yifei Lou , Jing Qin , Ming Yan

This paper describes a trapezoidal quadrature method for the discretization of singular and hypersingular boundary integral operators (BIOs) that arise in solving boundary value problems for elliptic partial differential equations. The…

Numerical Analysis · Mathematics 2022-09-07 Bowei Wu , Per-Gunnar Martinsson

We consider regular polynomial interpolation algorithms on recursively defined sets of interpolation points which approximate global solutions of arbitrary well-posed systems of linear partial differential equations. Convergence of the…

Numerical Analysis · Mathematics 2008-07-10 Joerg Kampen

In coherent diffractive imaging (CDI) the resolution of the reconstructed object is limited by the numerical aperture of the experimental setup. We present here a theoretical and numerical study for achieving super-resolution by…

Data Analysis, Statistics and Probability · Physics 2016-09-20 Tatiana Latychevskaia , Yuriy Chushkin , Hans-Werner Fink

This paper is concerned with recovering the solution of a final value problem associated with a parabolic equation involving a non linear source and a non-local term, which to the best of our knowledge has not been studied earlier. It is…

Numerical Analysis · Mathematics 2023-12-20 Subhankar Mondal

This paper addresses the problem of accurately estimating a function on one domain when only its discrete samples are available on another domain. To answer this challenge, we utilize a neural network, which we train to incorporate prior…

Machine Learning · Computer Science 2024-05-20 Guy Hay , Nir Sharon

The proximal gradient method is a generic technique introduced to tackle the non-smoothness in optimization problems, wherein the objective function is expressed as the sum of a differentiable convex part and a non-differentiable…

Numerical Analysis · Mathematics 2024-01-19 Abdeslem Hafid Bentbib , Khalide Jbilou , Ridwane Tahiri

Locally analytically, any isolated double point occurs as a double covering of a smooth surface. It can be desingularized via the canonical resolution, as it is well-known. In this paper we explicitly compute the fundamental cycle of both…

Algebraic Geometry · Mathematics 2007-05-23 Alberto Calabri , Rita Ferraro

The Inverse Problem for the estimation of a point-wise approximation error occurring at the discretization and solving of the system of partial differential equations is addressed. The set of the differences between the numerical solutions…

Numerical Analysis · Mathematics 2021-01-05 Aleksey Alekseev , Alexander Bondarev

We study inexact fixed-point proximity algorithms for solving a class of sparse regularization problems involving the $\ell_0$ norm. Specifically, the $\ell_0$ model has an objective function that is the sum of a convex fidelity term and a…

Optimization and Control · Mathematics 2024-04-30 Ronglong Fang , Yuesheng Xu , Mingsong Yan

This paper studies an optimal control problem governed by a semilinear elliptic equation, in which the control acts in a multiplicative or bilinear way as the reaction coefficient of the equation. We focus on the numerical discretization of…

Optimization and Control · Mathematics 2025-06-25 Eduardo Casas , Konstantinos Chrysafinos , Mariano Mateos

We present a new technique for the interpolation of discretely-sampled non-negat ive scalar fields across regions of missing data. Any set of basis functions can be used, though the method is fastest when they are close to orthogonal. We…

Astrophysics · Physics 2007-05-23 Will Saunders , Bill E. Ballinger

We study Tikhonov regularization for solving ill--posed operator equations where the solutions are functions defined on surfaces. One contribution of this paper is an error analysis of Tikhonov regularization which takes into account…

Numerical Analysis · Mathematics 2016-12-15 Guozhi Dong , Bert Juettler , Otmar Scherzer , Thomas Takacs
‹ Prev 1 4 5 6 7 8 10 Next ›