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Related papers: On Lebesgue Integral Quadrature

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An important application of Lebesgue integral quadrature arXiv:1807.06007 is developed. Given two random processes, $f(x)$ and $g(x)$, two generalized eigenvalue problems can be formulated and solved. In addition to obtaining two Lebesgue…

Numerical Analysis · Mathematics 2020-12-01 Vladislav Gennadievich Malyshkin

A method of deriving quadrature rules has been developed which gives nodes and weights for a Gaussian-type rule which integrates functions of the form: f(x,y,t) = a(x,y,t)/((x-t)^2+y^2) + b(x,y,t)/([(x-t)^2+y^2]^{1/2}) +…

Numerical Analysis · Mathematics 2010-09-21 Michael Carley

In this work we develop the Gaussian quadrature rule for weight functions involving fractional powers, exponentials and Bessel functions of the first kind. Besides the computation based on the use of the standard and the modified Chebyshev…

Numerical Analysis · Mathematics 2021-10-12 Eleonora Denich , Paolo Novati

Gauss quadrature integral approximation is extended to include integrals with a measure consisting of continuous as well as discrete components. That is, we give an approximation for the integral of a function plus its sum over a discrete…

Numerical Analysis · Mathematics 2023-06-12 A. D. Alhaidari

Estimates are obtained for the Lebesgue constants associated with the Gauss quadrature points on $(-1, +1)$ augmented by the point $-1$ and with the Radau quadrature points on either $(-1, +1]$ or $[-1, +1)$. It is shown that the Lebesgue…

Numerical Analysis · Mathematics 2018-09-17 William W. Hager , Hongyan Hou , Anil V. Rao

We consider the computation of quadrature rules that are exact for a Chebyshev set of linearly independent functions on an interval $[a,b]$. A general theory of Chebyshev sets guarantees the existence of rules with a Gaussian property, in…

Numerical Analysis · Mathematics 2017-11-01 Daan Huybrechs

Gaussian Quadrature is a well known technique for numerical integration. Recently Gaussian quadrature with respect to discrete measures corresponding to finite sums have found some new interest. In this paper we apply these ideas to…

Numerical Analysis · Mathematics 2007-05-23 Hartmut Monien

We investigate the numerical approximation of integrals over $\mathbb{R}^d$ equipped with the standard Gaussian measure $\gamma$ for integrands belonging to the Gaussian-weighted Sobolev spaces $W^\alpha_p(\mathbb{R}^d, \gamma)$ of mixed…

Numerical Analysis · Mathematics 2023-06-21 Dinh Dũng , Van Kien Nguyen

In 1973, E.J. McShane proposed an alternative definition of the Lebesgue integral based on Riemann sums, where gauges are used decide what tagged partitions are allowed. Such an approach does not require any preliminary knowledge of Measure…

Classical Analysis and ODEs · Mathematics 2018-07-20 Augusto C. Ponce , Jean Van Schaftingen

We develop efficient numerical integration methods for computing an integral whose integrand is a product of a smooth function and the Gaussian function with a small standard deviation. Traditional numerical integration methods applied to…

Numerical Analysis · Mathematics 2018-04-12 Yunyun Ma , Yuesheng Xu

We consider Choquet integrals with respect to dyadic Hausdorff content of non-negative functions which are not necessarily Lebesgue measurable. We study the theory of Lebesgue points. The studies yield convergence results and also a density…

Functional Analysis · Mathematics 2025-03-10 Petteri Harjulehto , Ritva Hurri-Syrjänen

Problems of interpolation, classification, and clustering are considered. In the tenets of Radon--Nikodym approach $\langle f(\mathbf{x})\psi^2 \rangle / \langle\psi^2\rangle$, where the $\psi(\mathbf{x})$ is a linear function on input…

Machine Learning · Computer Science 2021-09-14 Vladislav Gennadievich Malyshkin

Advancements in modern science have led to an increased prevalence of functional data, which are usually viewed as elements of the space of square-integrable functions $L^2$. Core methods in functional data analysis, such as functional…

Methodology · Statistics 2025-09-03 Su I Iao , Hans-Georg Müller

Gauss-Lobatto quadrature nodes and weights are optimal for closed summation-by-parts (SBP) formulations based on polynomial approximation spaces in the sense that for a prescribed function space they yield an SBP operator of minimal…

Numerical Analysis · Mathematics 2026-04-28 Nicholas Hale , Charis Harley , Prince Nchupang , Jan Nordström

A novel development is given of the theory of Gaussian quadrature, not relying on the theory of orthogonal polynomials. A method is given for computing the nodes and weights that is manifestly independent of choice of basis in the space of…

Numerical Analysis · Mathematics 2007-05-23 Ilan Degani , Jeremy Schiff

We consider two problems of estimation in high-dimensional Gaussian models. The first problem is that of estimating a linear functional of the means of $n$ independent $p$-dimensional Gaussian vectors, under the assumption that most of…

Statistics Theory · Mathematics 2018-11-12 Olivier Collier , Arnak S. Dalalyan

Highly oscillatory integrals of composite type arise in electronic engineering and their calculations is a challenging problem. In this paper, we propose two Gaussian quadrature rules for computing such integrals. The first one is…

Numerical Analysis · Mathematics 2025-04-01 Menghan Wu , Haiyong Wang

We present a systematic computational framework for generating positive quadrature rules in multiple dimensions on general geometries. A direct moment-matching formulation that enforces exact integration on polynomial subspaces yields…

Numerical Analysis · Computer Science 2018-09-03 Vahid Keshavarzzadeh , Robert M. Kirby , Akil Narayan

Given a non-archimedean real closed field with archimedean value group which contains the reals, we establish for the category of semialgebraic sets and functions a full Lebesgue measure and integration theory such that the main results…

Logic · Mathematics 2017-09-13 Tobias Kaiser

This article is concerned with Gaussian process quadratures, which are numerical integration methods based on Gaussian process regression methods, and sigma-point methods, which are used in advanced non-linear Kalman filtering and smoothing…

Methodology · Statistics 2015-04-24 Simo Särkkä , Jouni Hartikainen , Lennart Svensson , Fredrik Sandblom
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