English
Related papers

Related papers: Polynomial interpolation--regression on the sphere

200 papers

We study hyperinterpolation and its spectral multiplier variants on the sphere under weak cubature assumptions formulated through Sobolev discrepancy estimates. In contrast with classical hyperinterpolation theory, our framework does not…

Numerical Analysis · Mathematics 2026-05-19 Hao-Ning Wu

We develop and analyze a class of matrix-valued spherical-convolution kernels stemming from scaled zonal functions on $\mathbb{S}^2,$ the unit sphere embedded in $\mathbb{R}^3$. The construct of these kernels utilizes the Legendre…

Numerical Analysis · Mathematics 2026-05-08 Zhengjie Sun , Biao Huang , Xingping Sun

This paper studies the eigenvalue problem $K \psi = \lambda \psi$ associated with a Fredholm integral operator $K$ defined by a smooth kernel. The focus is on analyzing the convergence behaviour of numerical approximations to eigenvalues…

Numerical Analysis · Mathematics 2026-03-27 Shashank K. Shukla

We address the problem of approximating an unknown function from its discrete samples given at arbitrarily scattered sites. This problem is essential in numerical sciences, where modern applications also highlight the need for a solution to…

Numerical Analysis · Mathematics 2023-05-16 Nir Sharon , Rafael Sherbu Cohen , Holger Wendland

This work investigates the use of sparse polynomial interpolation as a model order reduction method for the incompressible Navier-Stokes equations. Numerical results are presented underscoring the validity of sparse polynomial…

Numerical Analysis · Mathematics 2022-01-11 Martin W. Hess , Gianluigi Rozza

We study the generalization error of functions that interpolate prescribed data points and are selected by minimizing a weighted norm. Under natural and general conditions, we prove that both the interpolants and their generalization errors…

Numerical Analysis · Mathematics 2021-02-11 Weilin Li

Kernel interpolation is a fundamental technique for approximating functions from scattered data, with a well-understood convergence theory when interpolating elements of a reproducing kernel Hilbert space. Beyond this classical setting,…

Numerical Analysis · Mathematics 2025-05-19 Toni Karvonen , Gabriele Santin , Tizian Wenzel

We obtain the asymptotic equalities for the least upper bounds of approximations by interpolation trigonometric polynomials with the equidistant nodes $x_k^{(n-1)}=\frac{2k\pi}{2n-1},\ k\in\mathbb{Z},$ in metrics of the spaces $L_p$ on…

Classical Analysis and ODEs · Mathematics 2018-06-08 A. S. Serdyuk , I. V. Sokolenko

This work is concerned with the kernel-based approximation of a complex-valued function from data, where the frequency response function of a partial differential equation in the frequency domain is of particular interest. In this setting,…

Computational Engineering, Finance, and Science · Computer Science 2024-11-26 Julien Bect , Niklas Georg , Ulrich Römer , Sebastian Schöps

This paper develops a fully discrete soft thresholding polynomial approximation over a general region, named Lasso hyperinterpolation. This approximation is an $\ell_1$-regularized discrete least squares approximation under the same…

Numerical Analysis · Mathematics 2021-08-31 Congpei An , Hao-Ning Wu

The paper deals with two fundamental types of trigonometric polynomials and splines on uniform grids, which allow us to construct interpolation approximations that depend linearly on the values of the interpolated function. Fundamental on…

Numerical Analysis · Mathematics 2019-12-05 V. P. Denysiuk

A method for moving least squares interpolation and differentiation is presented in the framework of orthogonal polynomials on discrete points. This yields a robust and efficient method which can avoid singularities and breakdowns in the…

Numerical Analysis · Mathematics 2010-09-21 Michael Carley

It is often possible to perform reduced order modelling by specifying linear subspace which accurately captures the dynamics of the system. This approach becomes especially appealing when linear subspace explicitly depends on parameters of…

Machine Learning · Computer Science 2026-04-17 Vladimir Fanaskov , Vladislav Trifonov , Alexander Rudikov , Ekaterina Muravleva , Ivan Oseledets

This paper focuses on the approximation of continuous functions on the unit sphere by spherical polynomials of degree $n$ via hyperinterpolation. Hyperinterpolation of degree $n$ is a discrete approximation of the $L^2$-orthogonal…

Numerical Analysis · Mathematics 2022-10-05 Congpei An , Hao-Ning Wu

We investigate an interpolation/extrapolation method that, given scattered observations of the Fourier transform, approximates its inverse. The interpolation algorithm takes advantage of modelling the available data via a shape-driven…

Numerical Analysis · Mathematics 2021-09-22 Emma Perracchione , Anna Maria Massone , Michele Piana

In the paper, the planar polynomial geometric interpolation of data points is revisited. Simple sufficient geometric conditions that imply the existence of the interpolant are derived in general. They require data points to be convex in a…

Numerical Analysis · Mathematics 2022-08-16 Jernej Kozak

In this paper, we propose a fully discrete soft thresholding trigonometric polynomial approximation on $[-\pi,\pi],$ named Lasso trigonometric interpolation. This approximation is an $\ell_1$-regularized discrete least squares approximation…

Numerical Analysis · Mathematics 2023-09-22 Congpei An , Mou Cai

The problem of interpolation at $(n+1)^2$ points on the unit sphere $\mathbb{S}^2$ by spherical polynomials of degree at most $n$ is proved to have a unique solution for several sets of points. The points are located on a number of circles…

Numerical Analysis · Mathematics 2007-05-23 Wolfgang zu Castell , Noemi Lain Fernandez , Yuan Xu

Inverse Vandermonde matrix calculation is a long-standing problem to solve nonsingular linear system $Vc=b$ where the rows of a square matrix $V$ are constructed by progression of the power polynomials. It has many applications in…

Numerical Analysis · Mathematics 2019-09-19 Mahdi S. Hosseini , Alfred Chen , Konstantinos N. Plataniotis

We introduce an algorithm of joint approximation of a function and its first derivative by alternative orthogonal polynomials on the interval [0,1].The algorithm exhibits properties of shape preserving approximation for the function. A weak…

Numerical Analysis · Mathematics 2020-01-14 Vladimir S. Chelyshkov