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We present a new rational approximation algorithm based on the empirical interpolation method for interpolating a family of parametrized functions to rational polynomials with invariant poles, leading to efficient numerical algorithms for…

Numerical Analysis · Mathematics 2025-01-23 Aidi Li , Yuwen Li

Diffusing a graph signal at multiple scales requires computing the action of the exponential of several multiples of the Laplacian matrix. We tighten a bound on the approximation error of truncated Chebyshev polynomial approximations of the…

Signal Processing · Electrical Eng. & Systems 2021-05-03 Sibylle Marcotte , Amélie Barbe , Rémi Gribonval , Titouan Vayer , Marc Sebban , Pierre Borgnat , Paulo Gonçalves

There is presented an approach to find an approximation polynomial of a function with two variables based on the two dimensional discrete Fourier transform. The approximation polynomial is expressed through Chebyshev polynomials. There is…

Numerical Analysis · Mathematics 2015-04-21 Ernest Scheiber

Previous works show convergence of rational Chebyshev approximants to the Pad\'e approximant as the underlying domain of approximation shrinks to the origin. In the present work, the asymptotic error and interpolation properties of rational…

Numerical Analysis · Mathematics 2024-10-08 Tobias Jawecki

We address the problem of the best uniform approximation by linear combinations of a finite system of functions. If the system is Chebyshev and the problem is unconstrained, then the classical Remez algorithm provides a fast and precise…

Numerical Analysis · Mathematics 2025-07-08 Vladimir Yu. Protasov , Rinat Kamalov

In a recent paper Lima, Panario and Wang have provided a new method to multiply polynomials in Chebyshev basis which aims at reducing the total number of multiplication when polynomials have small degree. Their idea is to use Karatsuba's…

Computational Complexity · Computer Science 2013-09-10 Pascal Giorgi

In this paper, we propose a new and simple approach to the approximation algorithms that are modified and improved from our published results. The computational and graphical examples are presented with the aid of Maple procedures.

Numerical Analysis · Mathematics 2025-06-24 Quan Le Phuong

As a measure of vertex importance according to the graph structure, PageRank has been widely applied in various fields. While many PageRank algorithms have been proposed in the past decades, few of them take into account whether the graph…

Networking and Internet Architecture · Computer Science 2023-03-07 Qi Zhang , Rongxia Tang , Zhengan Yao , Zanbo Zhang

Approximation theory plays a central role in numerical analysis, undergoing continuous evolution through a spectrum of methodologies. Notably, Lebesgue, Weierstrass, Fourier, and Chebyshev approximations stand out among these methods.…

Numerical Analysis · Mathematics 2024-04-30 S Akansha

Spectral polynomial approximation of smooth functions allows real-time manipulation of and computation with them, as in the Chebfun system. Extension of the technique to two-dimensional and three-dimensional functions on hyperrectangles has…

Numerical Analysis · Mathematics 2019-01-21 Kevin W. Aiton , Tobin A. Driscoll

This paper presents an algorithm to simulate Gaussian random vectors whose precision matrix can be expressed as a polynomial of a sparse matrix. This situation arises in particular when simulating Gaussian Markov random fields obtained by…

Methodology · Statistics 2020-04-07 Mike Pereira , Nicolas Desassis

This paper addresses the challenge of function approximation using Hermite interpolation on equally spaced nodes. In this setting, standard polynomial interpolation suffers from the Runge phenomenon. To mitigate this issue, we propose an…

Numerical Analysis · Mathematics 2024-09-06 Francesco Dell'Accio , Francisco Marcellán , Federico Nudo

In this paper we introduce a new family of wavelets, named Chebyshev wavelets, which are derived from conventional first and second kind Chebyshev polynomials. Properties of Chebyshev filter banks are investigated, including orthogonality…

Methodology · Statistics 2014-11-11 R. J. Cintra , H. M. de Oliveira , L. R. Soares

In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature address the consensus averaging problem by…

Information Theory · Computer Science 2009-11-13 Effrosyni Kokiopoulou , Pascal Frossard

We investigate deep composite polynomial approximations of continuous but non-differentiable functions with algebraic cusp singularities. The functions in focus consist of finitely many cusp terms of the form $|x-a_j|^{\alpha_j}$ with…

Numerical Analysis · Mathematics 2026-01-01 Kingsley Yeon , Steven B. Damelin , Michael Werman

This paper explores variants of the subspace iteration algorithm for computing approximate invariant subspaces. The standard subspace iteration approach is revisited and new variants that exploit gradient-type techniques combined with a…

Numerical Analysis · Mathematics 2024-05-14 Foivos Alimisis , Yousef Saad , Bart Vandereycken

We propose a fast and stable method for constructing matrix approximations to fractional integral operators applied to series in the Chebyshev fractional polynomials. This method utilizes a recurrence relation satisfied by the fractional…

Numerical Analysis · Mathematics 2025-10-31 Xiaolin Liu , Kuan Xu

It is a classical result in rational approximation theory that certain non-smooth or singular functions, such as $|x|$ and $x^{1/p}$, can be efficiently approximated using rational functions with root-exponential convergence in terms of…

Numerical Analysis · Mathematics 2025-06-27 Kingsley Yeon , Steven B. Damelin

Modeling spectral line profiles taking frequency redistribution effects into account is a notoriously challenging problem from the computational point of view, especially when polarization phenomena (atomic polarization and polarized…

Solar and Stellar Astrophysics · Physics 2021-01-04 A. Paganini , B. Hashemi , E. Alsina Ballester , L. Belluzzi

We study Chebyshev filter diagonalization as a tool for the computation of many interior eigenvalues of very large sparse symmetric matrices. In this technique the subspace projection onto the target space of wanted eigenvectors is…