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Unions of graph Fourier multipliers are an important class of linear operators for processing signals defined on graphs. We present a novel method to efficiently distribute the application of these operators to the high-dimensional signals…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-17 David I Shuman , Pierre Vandergheynst , Pascal Frossard

Chebyshev interpolation polynomials exhibit the exponential approximation property to analytic functions on a cube. Based on the Chebyshev interpolation polynomial approximation, we propose iterative polynomial approximation algorithms to…

Signal Processing · Electrical Eng. & Systems 2025-04-22 Cheng Cheng , Qiyu Sun , Cong Zheng

The focus of this article is the approximation of functions which are analytic on a compact interval except at the endpoints. Typical numerical methods for approximating such functions depend upon the use of particular conformal maps from…

Numerical Analysis · Mathematics 2014-05-05 Ben Adcock , Mark Richardson

Approximating a univariate function on the interval $[-1,1]$ with a polynomial is among the most classical problems in numerical analysis. When the function evaluations come with noise, a least-squares fit is known to reduce the effect of…

Numerical Analysis · Mathematics 2025-07-08 Takeru Matsuda , Yuji Nakatsukasa

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

In this paper we present an algorithm to fit data via exponentials when the error is measured using the max-norm. We prove the necesssary results to show that the algorithm will converge to the best approximation no matter the dataset.

We review the theory of optimal polynomial and rational Chebyshev approximations, and Zolotarev's formula for the sign function over the range (\epsilon \leq |z| \leq1). We explain how rational approximations can be applied to large sparse…

High Energy Physics - Lattice · Physics 2009-11-10 A. D. Kennedy

Efficient and stable algorithms for the calculation of spectral quantities and correlation functions are some of the key tools in computational condensed matter physics. In this article we review basic properties and recent developments of…

Other Condensed Matter · Physics 2007-05-23 Alexander Weisse , Gerhard Wellein , Andreas Alvermann , Holger Fehske

We study the solution set to multivariate Chebyshev approximation problem, focussing on the ill-posed case when the uniqueness of solutions can not be established via strict polynomial separation. We obtain an upper bound on the dimension…

Optimization and Control · Mathematics 2019-09-02 Vera Roshchina , Nadia Sukhorukova , Julien Ugon

The aim of the present work is to introduce a method based on Chebyshev polynomials for the numerical solution of a system of Cauchy type singular integral equations of the first kind on a finite segment. Moreover, an estimation error is…

Numerical Analysis · Mathematics 2015-08-11 Sedaghat Shahmorad , Samad Ahdiaghdam

We compare the convergence behavior of best polynomial approximations and Legendre and Chebyshev projections and derive optimal rates of convergence of Legendre projections for analytic and differentiable functions in the maximum norm. For…

Numerical Analysis · Mathematics 2021-12-30 Haiyong Wang

In this note we present a new special function that behaves like the error function and we provide an approximated accurate closed form for its CDF in terms of both Chebyshev polynomials of the first kind and the error function. Also, we…

General Mathematics · Mathematics 2025-12-30 Zeraoulia Rafik , Alvaro H Salas , David L Ocampo

We consider a discrete best approximation problem formulated in the framework of tropical algebra, which deals with the theory and applications of algebraic systems with idempotent operations. Given a set of samples of input and output of…

Numerical Analysis · Mathematics 2024-11-19 Nikolai Krivulin

The motivation of this paper is the development of an optimisation method for solving optimisation problems appearing in Chebyshev rational and generalised rational approximation problems, where the approximations are constructed as ratios…

Optimization and Control · Mathematics 2020-11-06 R. Díaz Millán , Nadezda Sukhorukova , Julien Ugon

Analytic expressions for the Fourier transforms of the Chebyshev and Legendre polynomials are derived, and the latter is used to find a new representation for the half-order Bessel functions. The numerical implementation of the so-called…

Numerical Analysis · Mathematics 2012-11-22 A. S. Fokas , S. A. Smitheman

Given a compact subset of a Banach space, the Chebyshev center problem consists of finding a minimal circumscribing ball containing the set. In this article we establish a numerically tractable algorithm for solving the Chebyshev center…

Optimization and Control · Mathematics 2023-07-06 Pradyumna Paruchuri , Debasish Chatterjee

The aim of this article is to study the role of piecewise implementation of Pad\'e-Chebyshev type approximation in minimising Gibbs phenomena in approximating piecewise smooth functions. A piecewise Pad\'e-Chebyshev type (PiPCT) algorithm…

Numerical Analysis · Mathematics 2019-10-24 S. Akansha , S. Baskar

Chebyshev spectral methods are widely used in numerical computations. When the underlying function has a singularity, it has been observed by L. N. Trefethen in 2011 that its Chebyshev interpolants exhibit an error localization property,…

Numerical Analysis · Mathematics 2023-06-09 Haiyong Wang

Chebyshev expansion coefficients can be computed efficiently by using the FFT, and for smooth functions the resulting approximation is close to optimal, with computations that are numerically stable. Given sufficiently accurate function…

Numerical Analysis · Mathematics 2015-03-30 Haiyong Wang , Daan Huybrechs

Piecewise Polynomials (PPs) are utilized in several engineering disciplines, like trajectory planning, to approximate position profiles given in the form of a set of points. While the approximation target along with domain-specific…

Machine Learning · Computer Science 2024-05-09 Hannes Waclawek , Stefan Huber