English
Related papers

Related papers: Remarkable upper bounds for the interpolation erro…

200 papers

For the quadratic Lagrange interpolation function, an algorithm is proposed to provide explicit and verified bound for the interpolation error constant that appears in the interpolation error estimation. The upper bound for the…

Numerical Analysis · Mathematics 2017-04-27 Xuefeng Liu , Chun'guang You

The quantitative estimation for the interpolation error constants of the Fujino-Morley interpolation operator is considered. To give concrete upper bounds for the constants, which is reduced to the problem of providing lower bounds for…

Numerical Analysis · Mathematics 2019-04-02 Shih-Kang Liao , Yu-Chen Shu , Xuefeng Liu

For the Lagrange interpolation over a triangular domain, we propose an efficient algorithm to rigorously evaluate the interpolation error constant under the maximum norm by using the finite element method (FEM). In solving the optimization…

Numerical Analysis · Mathematics 2021-12-07 Shirley Mae Galindo , Koichiro Ike , Xuefeng Liu

How good is a triangulation as an approximation of a smooth curved surface or manifold? We provide bounds on the {\em interpolation error}, the error in the position of the surface, and the {\em normal error}, the error in the normal…

Computational Geometry · Computer Science 2019-11-11 Marc Khoury , Jonathan Richard Shewchuk

We prove that a suitably adjusted version of Peter Jones' formula for interpolation by bounded holomorphic functions gives a sharp upper bound for what is known as the constant of interpolation. We show how this leads to precise and…

Complex Variables · Mathematics 2007-05-23 Artur Nicolau , Joaquim Ortega-Cerdà , Kristian Seip

Chebyshev interpolation is a highly effective, intensively studied method and enjoys excellent numerical properties. The interpolation nodes are known beforehand, implementation is straightforward and the method is numerically stable. For…

Numerical Analysis · Mathematics 2016-11-29 Kathrin Glau , Mirco Mahlstedt

In the error analysis of finite element methods, the shape regularity assumption on triangulations is typically imposed to obtain a priori error estimations. In practical computations, however, very thin or degenerated elements that violate…

Numerical Analysis · Mathematics 2022-02-03 Kenta Kobayashi , Takuya Tsuchiya

This paper deals with probabilistic upper bounds for the error in functional estimation defined on some interpolation and extrapolation designs, when the function to estimate is supposed to be analytic. The error pertaining to the estimate…

Statistics Theory · Mathematics 2011-01-26 Michel Broniatowski , Giorgio Celant , Marco Di Battista , Samuela Leoni-Aubin

An upper bound for the Lebesgue constant (the supremum norm) of the operator of interpolation of a function in equally spaced points of a triangle by a polynomial of total degree less than or equal to n is obtained. Earlier, the rate of…

Numerical Analysis · Mathematics 2022-09-22 N Baidakova

This article presents novel proof methods for estimating interpolation errors, predicated on the understanding that one has already studied foundational error analysis using the finite element method.

Numerical Analysis · Mathematics 2025-04-23 Hiroki Ishizaka

Only a few numerical methods can treat boundary value problems on polygonal and polyhedral meshes. The BEM-based Finite Element Method is one of the new discretization strategies, which make use of and benefits from the flexibility of these…

Numerical Analysis · Mathematics 2017-08-29 Steffen Weißer

We present the error analysis of Lagrange interpolation on triangles. A new \textit{a priori} error estimate is derived in which the bound is expressed in terms of the diameter and circumradius of a triangle. No geometric conditions on…

Numerical Analysis · Mathematics 2015-09-17 Kenta Kobayashi , Takuya Tsuchiya

The primary objective of this study is to develop novel interpolation operators that interpolate the boundary values of a function defined on a triangle. This is accomplished by constructing New Generalized Boolean sum neural network…

Numerical Analysis · Mathematics 2024-10-07 Aaqib Ayoub Bhat , Asif Khan

The distance between the true and numerical solutions in some metric is considered as the discretization error magnitude. If error magnitude ranging is known, the triangle inequality enables the estimation of the vicinity of the approximate…

Computational Physics · Physics 2018-05-11 A. K. Alekseev , A. E. Bondarev , I. M. Navon

We prove stability bounds for Stokes-like virtual element spaces in two and three dimensions. Such bounds are also instrumental in deriving optimal interpolation estimates. Furthermore, we develop some numerical tests in order to…

Numerical Analysis · Mathematics 2022-12-07 L. Beirão da Veiga , L. Mascotto , J. Meng

We study in this paper the function approximation error of linear interpolation and extrapolation. Several upper bounds are presented along with the conditions under which they are sharp. All results are under the assumptions that the…

Numerical Analysis · Mathematics 2022-09-27 Liyuan Cao , Zaiwen Wen , Ya-xiang Yuan

We present a Hermite interpolation problem via splines of odd-degree which, to the best knowledge of the authors, has not been considered in the literature on interpolation via odd-degree splines. In this new interpolation problem, we…

Statistics Theory · Mathematics 2007-06-13 Fadoua Balabdaoui , Jon A. Wellner

We propose a method for computing upper bounds for the Heilbronn problem for triangles.

Computational Geometry · Computer Science 2010-03-09 Francesco De Comite , Jean-Paul Delahaye

In the recent paper [8], a new method to compute stable kernel-based interpolants has been presented. This \textit{rescaled interpolation} method combines the standard kernel interpolation with a properly defined rescaling operation, which…

Numerical Analysis · Mathematics 2018-10-31 Stefano De Marchi , Andrea Idda , Gabriele Santin

Effective verification and validation techniques for modern scientific machine learning workflows are challenging to devise. Statistical methods are abundant and easily deployed, but often rely on speculative assumptions about the data and…

Machine Learning · Computer Science 2025-02-11 Tyler Chang , Andrew Gillette , Romit Maulik
‹ Prev 1 2 3 10 Next ›