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Approximate solutions of linear and nonlinear integral equations using methods related to an interpolatory projection involve many integrals which need to be evaluated using a numerical quadrature formula. In this paper, we consider…

Numerical Analysis · Mathematics 2017-08-03 Rekha P. Kulkarni , Gobinda Rakshit

We consider a Urysohn integral operator $\mathcal{K}$ with kernel of the type of Green's function. For $r \geq 1$, a space of piecewise polynomials of degree $\leq r-1 $ with respect to a uniform partition is chosen to be the approximating…

Numerical Analysis · Mathematics 2021-10-26 Gobinda Rakshit , Akshay S. Rane , Kshitij Patil

Consider a Urysohn integral equation $x - \mathcal{K} (x) = f$, where $f$ and the integral operator $\mathcal{K}$ with kernel of the type of Green's function are given. In the computation of approximate solutions of the given integral…

Numerical Analysis · Mathematics 2023-01-10 Gobinda Rakshit

In this paper we investigate the use of Richardson extrapolation to estimate the convergence rates for numerical solutions to advection problems involving discontinuities. We use modified equation analysis to describe the expectation of the…

Numerical Analysis · Mathematics 2013-02-05 J. W. Banks , T. D. Aslam

In this paper we propose projection methods based on spline quasi-interpolating projectors of degree $d$ and class $C^{d-1}$ on a bounded interval for the numerical solution of nonlinear integral equations. We prove that they have high…

Numerical Analysis · Mathematics 2018-02-15 Catterina Dagnino , Angelo Dallefrate , Sara Remogna

Richardson extrapolation is a classical technique from numerical analysis that can improve the approximation error of an estimation method by combining linearly several estimates obtained from different values of one of its hyperparameters,…

Machine Learning · Computer Science 2020-07-20 Francis Bach

We prove the convergence of an incremental projection numerical scheme for the time-dependent incompressible Navier--Stokes equations, without any regularity assumption on the weak solution. The velocity and the pressure are discretised in…

Numerical Analysis · Mathematics 2023-06-30 Robert Eymard , David Maltese

Interpolation-based methods are well-established and effective approaches for the efficient generation of accurate reduced-order surrogate models. Common challenges for such methods are the automatic selection of good or even optimal…

Numerical Analysis · Mathematics 2024-07-23 Quirin Aumann , Steffen W. R. Werner

The (conditional or unconditional) distribution of the continuous scan statistic in a one-dimensional Poisson process may be approximated by that of a discrete analogue via time discretization (to be referred to as the discrete…

Probability · Mathematics 2016-02-09 Yi-Ching Yao , Daniel Wei-Chung Miao , Xenos Chang-Shuo Lin

In this paper, we derive an asymptotic error expansion for the eigenvalue approximations by the lowest order Raviart-Thomas mixed finite element method for the general second order elliptic eigenvalue problems. Extrapolation based on such…

Numerical Analysis · Mathematics 2011-01-11 Hehu Xie

Consider a linear operator equation $x - Kx = f$, where $f$ is given and $K$ is a Fredholm integral operator with a Green's function type kernel defined on $C[0, 1]$. For $r \geq 0$, we employ the interpolatory projection at $2r + 1$…

Numerical Analysis · Mathematics 2026-02-20 Gobinda Rakshit , Shashank K. Shukla , Akshay S. Rane

We study numerical integration of smooth functions defined over the $s$-dimensional unit cube. A recent work by Dick et al. (2019) has introduced so-called extrapolated polynomial lattice rules, which achieve the almost optimal rate of…

Numerical Analysis · Mathematics 2020-07-15 Takashi Goda

This paper develops the process of using Richardson Extrapolation to improve the Kernel Density Estimation method, resulting in a more accurate (lower Mean Squared Error) estimate of a probability density function for a distribution of data…

Probability · Mathematics 2018-12-21 Ruben G. Ascoli

In this paper we study linear projection methods for approximating the solution and simultaneously preserving first integrals of autonomous ordinary differential equations. We show that (linear) projection methods are a subset of discrete…

Numerical Analysis · Mathematics 2015-11-05 R. A. Norton , D. I. McLaren , G. R. W. Quispel , A. Stern , A. Zanna

This paper deals with a modified iterative projection method for approximating a solution of the hierarchical fixed point problem for a sequene of nearly nonexpansive mappings with respect to a nonexpansive mapping. It is shown that under…

Functional Analysis · Mathematics 2014-03-14 Ibrahim Karahan , Murat Ozdemir

In this study, we employ Euler's method and Richardson's extrapolation to solve a triple integral, which is then transformed into a third-order initial value problem. Our objective is to resolve the computational challenges associated with…

Numerical Analysis · Mathematics 2026-02-17 Shubhangini Gupta , Prashant Sharma , Tamal Pramanick

This paper uses the Modified Projection Method to examine the errors in solving the boundary integral equation from Laplace equation. The analysis uses weighted norms, and parallel algorithms help solve the independent linear systems. By…

Numerical Analysis · Mathematics 2024-11-04 Akshay Rane , Kunalkumar Shelar

Discrete regularization methods are often applied for obtaining stable approximate solutions for ill-posed operator equations $Tx=y$, where $T: X\to Y$ is a bounded operator between Hilbert spaces with non-closed range $R(T)$ and $y\in…

Functional Analysis · Mathematics 2016-07-01 M Thamban Nair

We propose an extrapolation technique that allows accuracy improvement of the discrete dipole approximation computations. The performance of this technique was studied empirically based on extensive simulations for 5 test cases using many…

Optics · Physics 2008-07-29 Maxim A. Yurkin , Valeri P. Maltsev , Alfons G. Hoekstra

The aim of this paper is to derive a refined first-order expansion formula in Rn, the goal being to get an optimal reduced remainder, compared to the one obtained by usual Taylor's formula. For a given function, the formula we derived is…

Numerical Analysis · Mathematics 2022-10-03 Joel Chaskalovic , Franck Assous
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