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We present a method for computing nearly singular integrals that occur when single or double layer surface integrals, for harmonic potentials or Stokes flow, are evaluated at points nearby. Such values could be needed in solving an integral…

Numerical Analysis · Mathematics 2024-06-21 J. Thomas Beale , Svetlana Tlupova

Soft extrapolation refers to the problem of recovering a function from its samples, multiplied by a fast-decaying window and perturbed by an additive noise, over an interval which is potentially larger than the essential support of the…

Numerical Analysis · Mathematics 2018-12-26 Dmitry Batenkov , Laurent Demanet , Hrushikesh N. Mhaskar

Wave equations help us to understand phenomena ranging from earthquakes to tsunamis. These phenomena materialise over very large scales. It would be computationally infeasible to track them over a regular mesh. Yet, since the phenomena are…

Computational Engineering, Finance, and Science · Computer Science 2025-04-24 Timothy Stokes , Tobias Weinzierl , Han Zhang , Baojiu Li

In this paper we prove an optimal error estimate for the H(curl)-conforming projection based p-interpolation operator introduced in [L. Demkowicz and I. Babuska, p interpolation error estimates for edge finite elements of variable order in…

Numerical Analysis · Mathematics 2009-03-27 Alexei Bespalov , Norbert Heuer

We derive $H_{\text{curl}}$-error estimates and improved $L^2$-error estimates for the Maxwell equations approximated using edge finite elements. These estimates only invoke the expected regularity pickup of the exact solution in the scale…

Numerical Analysis · Mathematics 2017-10-17 Alexandre Ern , Jean-Luc Guermond

We consider finite element approximations of ill-posed elliptic problems with conditional stability. The notion of {\emph{optimal error estimates}} is defined including both convergence with respect to mesh parameter and perturbations in…

Numerical Analysis · Mathematics 2024-03-25 Erik Burman , Mihai Nechita , Lauri Oksanen

We consider a broad class of first-order optimization algorithms which are \emph{oblivious}, in the sense that their step sizes are scheduled regardless of the function under consideration, except for limited side-information such as…

Optimization and Control · Mathematics 2016-05-12 Yossi Arjevani , Ohad Shamir

We adapt Schaback's error doubling trick [R. Schaback. Improved error bounds for scattered data interpolation by radial basis functions. Math. Comp., 68(225):201--216, 1999.] to give error estimates for radial interpolation of functions…

Numerical Analysis · Mathematics 2007-12-02 R. A. Brownlee , E. H. Georgoulis , J. Levesley

Radial basis functions (RBFs) are prominent examples for reproducing kernels with associated reproducing kernel Hilbert spaces (RKHSs). The convergence theory for the kernel-based interpolation in that space is well understood and optimal…

Classical Analysis and ODEs · Mathematics 2023-09-15 Thomas Hangelbroek , Christian Rieger

For the quadratic Lagrange interpolation function, an algorithm is proposed to provide explicit and verified bound for the interpolation error constant that appears in the interpolation error estimation. The upper bound for the…

Numerical Analysis · Mathematics 2017-04-27 Xuefeng Liu , Chun'guang You

We prove an extrapolation result for general operators under some weak assumptions on the boundedness of the operator. In particular, we show that if the operator is weakly bounded on some L^{p_{0}}(w), for all "flat" weights, w in…

Classical Analysis and ODEs · Mathematics 2012-04-19 Nicholas Boros , Nikolaos Pattakos , Alexander Volberg

This paper studies the influence of scaling on the behavior of Radial Basis Function interpolation. It focuses on certain central aspects, but does not try to be exhaustive. The most important questions are: How does the error of a…

Numerical Analysis · Mathematics 2022-10-12 Elisabeth Larsson , Robert Schaback

This paper studies the lower bound complexity for the optimization problem whose objective function is the average of $n$ individual smooth convex functions. We consider the algorithm which gets access to gradient and proximal oracle for…

Optimization and Control · Mathematics 2019-08-23 Guangzeng Xie , Luo Luo , Zhihua Zhang

We show that for integral operators of general form the norm bounds in Lorentz spaces imply certain norm bounds for the maximal function. As a consequence, the a.e. convergence for the integral operators on the Lorentz spaces follows from…

Classical Analysis and ODEs · Mathematics 2008-02-03 Alexander Kiselev

An upper bound for the Lebesgue constant (the supremum norm) of the operator of interpolation of a function in equally spaced points of a triangle by a polynomial of total degree less than or equal to n is obtained. Earlier, the rate of…

Numerical Analysis · Mathematics 2022-09-22 N Baidakova

An effective approach for construction of simple approximation for description of non-ideality effects in classical one- and two-component plasma model is under discussion. General constraints i.e. positiveness and exponential type for…

Plasma Physics · Physics 2009-03-31 Victor Gryaznov , Igor Iosilevskiy

We estimate the Lebesgue constants for Lagrange interpolation processes on one or several intervals by rational functions with fixed poles. We admit that the poles have accumulation points on the intervals. To prove it we use an analog of…

Complex Variables · Mathematics 2024-06-19 Sergei Kalmykov , Alexey Lukashov

Approximation properties of the expansions $\sum_{k\in{\mathbb z}^d}c_k\phi(M^jx+k)$, where $M$ is a matrix dilation, $c_k$ is either the sampled value of a signal $f$ at $M^{-j}k$ or the integral average of $f$ near $M^{-j}k$ (falsified…

Functional Analysis · Mathematics 2014-07-02 A. Krivoshein , M. Skopina

In this paper we present a second-order and continuous interpolation algorithm for cell-centered adaptive-mesh-refinement (AMR) grids. Continuity requirement poses a non-trivial problem at resolution changes. We develop a classification of…

Computational Physics · Physics 2016-05-04 Dmitry Borovikov , Igor V. Sokolov , Gabor Toth

This paper introduces the concept of hyperpolation: a way of generalising from a limited set of data points that is a peer to the more familiar concepts of interpolation and extrapolation. Hyperpolation is the task of estimating the value…

Machine Learning · Computer Science 2024-10-15 Toby Ord