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Related papers: Fast transforms for high order boundary conditions

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We present a new fast solver to calculate fixed-boundary plasma equilibria in toroidally axisymmetric geometries. By combining conformal mapping with Fourier and integral equation methods on the unit disk, we show that high-order accuracy…

This paper deals with the problem of reconstructing a band-limited signal when a finite subset of its samples and of its derivative are missing. The technique used, due to P.J.S.G. Ferreira, is based on the use of a particular frame for…

Functional Analysis · Mathematics 2010-09-13 Paola Brianzi , Vincenza Del Prete

We are interested in fast and stable iterative regularization methods for image deblurring problems with space invariant blur. The associated coefficient matrix has a Block Toeplitz Toeplitz Blocks (BTTB) like structure plus a small rank…

Numerical Analysis · Mathematics 2020-09-07 Davide Bianchi , Alessandro Buccini

Inverse problems arise in a wide spectrum of applications in fields ranging from engineering to scientific computation. Connected with the rise of interest in inverse problems is the development and analysis of regularization methods, such…

Numerical Analysis · Mathematics 2025-05-12 Abinash Nayak

Recently, sparsity-based algorithms are proposed for super-resolution spectrum estimation. However, to achieve adequately high resolution in real-world signal analysis, the dictionary atoms have to be close to each other in frequency,…

Machine Learning · Statistics 2015-06-05 Yiyuan She , Huanghuang Li , Jiangping Wang , Dapeng Wu

This work aims to accelerate the convergence of proximal gradient methods used to solve regularized linear inverse problems. This is achieved by designing a polynomial-based preconditioner that targets the eigenvalue spectrum of the normal…

Inspired by the theoretical results on optimal preconditioning stated by Ng, R.Chan, and Tang in the framework of Reflective boundary conditions (BCs), in this paper we present analogous results for Anti-Reflective BCs, where an additional…

Numerical Analysis · Mathematics 2012-11-05 Pietro Dell'Acqua , Stefano Serra-Capizzano , Cristina Tablino Possio

In a recent article the authors showed that the radiative Transfer equations with multiple frequencies and scattering can be formulated as a nonlinear integral system. In the present article, the formulation is extended to handle reflective…

Numerical Analysis · Mathematics 2023-06-12 Olivier Pironneau , Pierre-Henri Tournier

This article is a direct continuation of [1] where we begun the study of the transfer matrix spectral problem for the cyclic representations of the trigonometric 6-vertex reflection algebra associated to the Bazhanov-Stroganov Lax operator.…

Mathematical Physics · Physics 2018-09-26 J. M. Maillet , G. Niccoli , B. Pezelier

We consider radial complex scaling/perfectly matched layer methods for scalar resonance problems in homogeneous exterior domains. We introduce a new abstract framework to analyze the convergence of domain truncations and discretizations.…

Numerical Analysis · Mathematics 2020-07-21 Martin Halla

We present a new high-order accurate spectral element solution to the two-dimensional scalar Poisson equation subject to a general Robin boundary condition. The solution is based on a simplified version of the shifted boundary method…

Numerical Analysis · Mathematics 2023-10-27 Jens Visbech , Allan Peter Engsig-Karup , Mario Ricchiuto

Translations or, more generally, coordinate transformations of scalar fields arise in several applications, such as weather, accretion disk and magnetized plasma turbulence modeling. In local studies of accretion disks and magnetized…

Plasma Physics · Physics 2021-10-07 Manaure Francisquez , Noah R. Mandell , Ammar Hakim , Gregory W. Hammett

This paper presents a couple of preconditioning techniques that can be used to enhance the performance of iterative regularization methods applied to image deblurring problems with a variety of point spread functions (PSFs) and boundary…

Numerical Analysis · Mathematics 2022-12-13 Marco Donatelli , Paola Ferrari , Silvia Gazzola

Many interesting and fundamentally practical optimization problems, ranging from optics, to signal processing, to radar and acoustics, involve constraints on the Fourier transform of a function. It is well-known that the {\em fast Fourier…

Optimization and Control · Mathematics 2012-09-05 Robert J. Vanderbei

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

Dictionary learning is the task of determining a data-dependent transform that yields a sparse representation of some observed data. The dictionary learning problem is non-convex, and usually solved via computationally complex iterative…

Machine Learning · Computer Science 2016-11-30 Cristian Rusu , Nuria Gonzalez-Prelcic , Robert Heath

In this article, we discuss the efficient ways of implementing the transparent boundary condition (TBC) and its various approximations for the free Schr\"{o}dinger equation on a hyperrectangular computational domain in $\field{R}^d$ with…

Numerical Analysis · Mathematics 2024-08-27 Samardhi Yadav , Vishal Vaibhav

Conditional stability estimates require additional regularization for obtaining stable approximate solutions if the validity area of such estimates is not completely known. In this context, we consider ill-posed nonlinear inverse problems…

Numerical Analysis · Mathematics 2020-01-29 Frank Werner , Bernd Hofmann

We consider the monotone inclusion problems in real Hilbert spaces. Proximal splitting algorithms are very popular technique to solve it and generally achieve weak convergence under mild assumptions. Researchers assume the strong conditions…

Optimization and Control · Mathematics 2022-05-05 Avinash Dixit , D. R. Sahu , Pankaj Gautam , T. Som

The theory of spectral filtering is a remarkable tool to understand the statistical properties of learning with kernels. For least squares, it allows to derive various regularization schemes that yield faster convergence rates of the excess…

Machine Learning · Computer Science 2021-11-11 Gaspard Beugnot , Julien Mairal , Alessandro Rudi