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The paper deals with a special filtered approximation method, which originates interpolation polynomials at Chebyshev zeros by using de la Vall\'ee Poussin filters. These polynomials can be an useful device for many theoretical and…

Numerical Analysis · Mathematics 2020-08-04 Donatella Occorsio , Woula Themistoclakis

Starting from de la Vall\'ee Poussin type (VP) interpolation, the authors have recently introduced a family of interpolating polynomial scaling and wavelet bases generating the approximation and detail spaces of a non-standard…

Numerical Analysis · Mathematics 2026-02-25 Woula Themistoclakis , Marc Van Barel

We present a new image scaling method both for downscaling and upscaling, running with any scale factor or desired size. The resized image is achieved by sampling a bivariate polynomial which globally interpolates the data at the new scale.…

Computer Vision and Pattern Recognition · Computer Science 2022-07-11 Donatella Occorsio , Giuliana Ramella , Woula Themistoclakis

This paper offers a newly created integral approach for operators employing the orthogonal modified Laguerre polynomials and P\u{a}lt\u{a}nea basis. These operators approximate the functions over the interval $[0,\infty)$. Further, the…

Functional Analysis · Mathematics 2024-05-14 Kapil Kumar , Naokant Deo , Durvesh Kumar Verma

This paper analyzes a method to approximate the first passage time probability density function which turns to be particularly useful if only sample data are available. The method relies on a Laguerre-Gamma polynomial approximation and…

Probability · Mathematics 2022-12-14 Elvira Di Nardo , Giuseppe D'Onofrio , Tommaso Martini

The theory of Chebyshev approximation has been extensively studied. In most cases, the optimality conditions are based on the notion of alternance or alternating sequence (that is, maximal deviation points with alternating deviation signs).…

Functional Analysis · Mathematics 2025-01-30 Nadezda Sukhorukova , Julien Ugon

We propose a new sampling-based approach for approximate inference in filtering problems. Instead of approximating conditional distributions with a finite set of states, as done in particle filters, our approach approximates the…

Machine Learning · Computer Science 2020-03-03 Xuan Su , Wee Sun Lee , Zhen Zhang

We consider polynomial approximation over the interval $[-1,1]$ by regularized weighted discrete least squares methods with $\ell_2-$ or $\ell_1-$regularization, respectively. As the set of nodes we use Gauss quadrature points (which are…

Numerical Analysis · Mathematics 2019-08-27 Congpei An , Hao-Ning Wu

This paper considers filtered polynomial approximations on the unit sphere $\mathbb{S}^d\subset \mathbb{R}^{d+1}$, obtained by truncating smoothly the Fourier series of an integrable function $f$ with the help of a "filter" $h$, which is a…

Classical Analysis and ODEs · Mathematics 2015-09-15 Heping Wang , Ian H. Sloan

This paper investigates the potential applications of a parametric family of polynomial wavelets that has been recently introduced starting from de la Vall\'ee Poussin (VP) interpolation at Chebyshev nodes. Unlike classical wavelets, which…

Numerical Analysis · Mathematics 2026-01-22 Mariantonia Cotronei , Woula Themistoclakis , Marc Van Barel

A product quadrature rule, based on the filtered de la Vall\'ee Poussin polynomial approximation, is proposed for evaluating the finite Hilbert transform in [-1; 1]. Convergence results are stated in weighted uniform norm for functions…

Numerical Analysis · Mathematics 2021-09-23 D. Occorsio , M. G. Russo , W. Themistoclakis

We consider the problem of approximating a truncated Gaussian kernel using Fourier (trigonometric) functions. The computation-intensive bilateral filter can be expressed using fast convolutions by applying such an approximation to its range…

Image and Video Processing · Electrical Eng. & Systems 2018-11-07 Sanjay Ghosh , Pravin Nair , Kunal N. Chaudhury

In the paper, we propose two new conjectures about the convergence of Hermite Approximants of multivalued analytic functions of Laguerre class ${\mathscr L}$. The conjectures are based in part on the numerical experiments, made recently by…

Complex Variables · Mathematics 2016-03-11 Nikolay R. Ikonomov , Ralitza K. Kovacheva , Sergey P. Suetin

The theory of viscosity solutions has been effective for representing and approximating weak solutions to fully nonlinear Partial Differential Equations (PDEs) such as the elliptic Monge-Amp\`ere equation. The approximation theory of…

Numerical Analysis · Mathematics 2012-12-05 Brittany D. Froese , Adam M. Oberman

In this paper, we consider Wiener filters to reconstruct deterministic and (wide-band) stationary graph signals from their observations corrupted by random noises, and we propose distributed algorithms to implement Wiener filters and…

Signal Processing · Electrical Eng. & Systems 2022-05-10 Cong Zheng , Cheng Cheng , Qiyu Sun

Trigonometric polynomials are widely used for the approximation of a smooth function $f$ from a set of nonuniformly spaced samples $\{f(x_j)\}_{j=0}^{N-1}$. If the samples are perturbed by noise, controlling the smoothness of the…

Numerical Analysis · Mathematics 2025-10-20 Thomas Strohmer

In this contribution we deal with Gaussian quadrature rules based on orthogonal polynomials associated with a weight function $w(x)= x^{\alpha} e^{-x}$ supported on an interval $(0,z)$, $z>0.$ The modified Chebyshev algorithm is used in…

Numerical Analysis · Mathematics 2024-01-05 Juan C. García-Ardila , Francisco Marcellán

Laguerre polynomials are orthogonal polynomials defined on positive half line with respect to weight $e^{-x}$. They have wide applications in scientific and engineering computations. However, the exponential growth of Laguerre polynomials…

Numerical Analysis · Mathematics 2026-05-18 Shenghe Huang , Haijun Yu

Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite-dimensional functions from limited samples. This is a key task in computational science and engineering, e.g., surrogate modelling in…

Numerical Analysis · Mathematics 2023-11-08 Ben Adcock , Simone Brugiapaglia , Nick Dexter , Sebastian Moraga

We study linear polynomial approximation of functions in weighted Sobolev spaces $W^r_{p,w}(\mathbb{R}^d)$ of mixed smoothness $r \in \mathbb{N}$, and their optimality in terms of Kolmogorov and linear $n$-widths of the unit ball…

Numerical Analysis · Mathematics 2025-01-03 Dinh Dũng
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