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In some fields such as Mathematics Mechanization, automated reasoning and Trustworthy Computing etc., exact results are needed. Symbolic computations are used to obtain the exact results. Symbolic computations are of high complexity. In…

Symbolic Computation · Computer Science 2008-09-10 Yong Feng , Jingzhong Zhang , Xiaolin Qin , Xun Yuan

We propose novel methods for approximate sampling recovery and integration of functions in the Freud-weighted Sobolev space $W^r_{p,w}(\mathbb{R})$. The approximation error of sampling recovery is measured in the norm of the Freud-weighted…

Numerical Analysis · Mathematics 2026-01-06 Dinh Dũng

Interpolation of classes of differentiated functions given on a finite interval by trigonometric splines using the phantom node method is considered. This method consists in supplementing a given sequence of values of an approximate…

Numerical Analysis · Mathematics 2021-12-17 Volodymyr Denysiuk , Olena Hryshko

In this paper, we propose an interpolation formula for periodic functions. This formula can be regarded as an analog of the Sinc approximation, which is an interpolation formula for functions defined on the entire infinite interval.…

Numerical Analysis · Mathematics 2019-09-10 Hidenori Ogata

The aim of this paper is to study the approximation of functions using a higher order Hermite-Fejer interpolation process on the unit circle. The system of nodes is composed of vertically projected zeros of Jacobi polynomials onto the unit…

Numerical Analysis · Mathematics 2022-03-01 Swarnima Bahadur , Varun

The need to approximate functions is ubiquitous in science, either due to empirical constraints or high computational cost of accessing the function. In high-energy physics, the precise computation of the scattering cross-section of a…

High Energy Physics - Phenomenology · Physics 2022-06-08 Ibrahim Chahrour , James D. Wells

This paper presents a complete Pascal interpolation scheme for use in the plane geometry mapping applied in association with numerical methods. The geometry of a domain element is approximated by a complete Pascal polynomial. The…

Numerical Analysis · Computer Science 2019-03-11 Sulaiman Y. Abo Diab

There is proposed a method for improving the convergence of Fourier series by function systems, orthogonal at the segment, the application of which allows for smooth functions to receive uniformly convergent series. There is also proposed…

Numerical Analysis · Mathematics 2018-05-18 Volodymyr Denysiuk

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

In this paper, we introduce a superconvergent approximation method that employs radial basis functions (RBFs) in the numerical solution of conservation laws. The use of RBFs for interpolation and approximation is a well developed area of…

Numerical Analysis · Mathematics 2021-06-21 Andrew Christlieb , William Sands , Hyoseon Yang

In this paper we consider the approximation of functions by radial basis function interpolants. There is a plethora of results about the asymptotic behaviour of the error between appropriately smooth functions and their interpolants, as the…

Numerical Analysis · Mathematics 2007-12-02 R. A. Brownlee , W. A. Light

An adaptive interpolation scheme is proposed to accurately calculate the wideband responses in electromagnetic simulations. In the proposed scheme, the sampling points are first carefully divided into several groups based on their responses…

Computational Engineering, Finance, and Science · Computer Science 2022-03-14 Kai Zhu , Jinhui Wang , Shunchuan Yang

We present a nonlinear interpolation technique for parametric fields that exploits optimal transportation of coherent structures of the solution to achieve accurate performance. The approach generalizes the nonlinear interpolation procedure…

Numerical Analysis · Mathematics 2023-10-09 Simona Cucchiara , Angelo Iollo , Tommaso Taddei , Haysam Telib

Probabilistic graphical models are a key tool in machine learning applications. Computing the partition function, i.e., normalizing constant, is a fundamental task of statistical inference but it is generally computationally intractable,…

Machine Learning · Statistics 2020-01-29 Sungsoo Ahn , Michael Chertkov , Adrian Weller , Jinwoo Shin

This paper deals with the kernel-based approximation of a multivariate periodic function by interpolation at the points of an integration lattice -- a setting that, as pointed out by Zeng, Leung, Hickernell (MCQMC2004, 2006) and Zeng,…

Numerical Analysis · Mathematics 2022-01-25 Vesa Kaarnioja , Yoshihito Kazashi , Frances Y. Kuo , Fabio Nobile , Ian H. Sloan

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

The semi-Lagrangian method using the hybrid-cubic-rational interpolation function [M. Ida, Comput. Fluid Dyn. J. 10 (2001) 159] is modified to a conservative method by incorporating the concept discussed in [R. Tanaka et al., Comput. Phys.…

Numerical Analysis · Mathematics 2025-10-20 Masato Ida

We show that the modulus of an inner function can be uniformly approximated in the unit disk by the modulus of an interpolating Blaschke product.

Classical Analysis and ODEs · Mathematics 2007-05-23 Geir Arne Hjelle , Artur Nicolau

This paper presents a super-resolution method based on gradient-based adaptive interpolation. In this method, in addition to considering the distance between the interpolated pixel and the neighboring valid pixel, the interpolation…

Multimedia · Computer Science 2009-03-25 Jinyu Chu , Ju Liu , Jianping Qiao , Xiaoling Wang , Yujun Li

An algorithm for computing an analytic function of a matrix $A$ is described. The algorithm is intended for the case where $A$ has some close eigenvalues, and clusters (subsets) of close eigenvalues are separated from each other. This…

Numerical Analysis · Mathematics 2023-12-13 V. G. Kurbatov , I. V. Kurbatova
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