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Application a Taylor series to approximate a function with large gradients Full article

Journal Сибирские электронные математические известия (Siberian Electronic Mathematical Reports)
, E-ISSN: 1813-3304
Output data Year: 2023, Volume: 20, Number: 2, Pages: 1420-1429 Pages count : 10 DOI: 10.33048/semi.2023.20.087
Tags function of one or two variables with large gradients, boundary layer component, Taylor series approximation, modi cation, error estimation
Authors Zadorin A.I. 1
Affiliations
1 Sobolev Institute of Mathematics

Funding (1)

1 Омский филиал ФГБУН «Институт математики им. С.Л. Соболева СО РАН». FWNF-2022-0016

Abstract: The method of approximating functions by polynomials based on Taylor series expansion is widely known. However, the residual term of such an approximation can be significant if the function has large gradients. The work assumes that the function has a decomposition in the form of a sum of regular and boundary layer components. The boundary layer component is a function of general form, known up to a factor, and is responsible for large gradients of the given function. This decomposition is valid, in particular, for the solution of a singularly perturbed problem. To approximate the function, a formula is proposed that uses the Taylor series expansion of the function and is exact for the boundary layer component. Under certain restrictions on the boundary layer component, estimates of the error in the approximation of the function are obtained. These estimates depend only on the regular component. Cases of functions of one and two variables are considered.
Cite: Zadorin A.I.
Application a Taylor series to approximate a function with large gradients
Сибирские электронные математические известия (Siberian Electronic Mathematical Reports). 2023. V.20. N2. P.1420-1429. DOI: 10.33048/semi.2023.20.087 WOS Scopus РИНЦ
Dates:
Submitted: Oct 15, 2023
Published print: Dec 12, 2023
Published online: Dec 12, 2023
Identifiers:
Web of science: WOS:001164415800009
Scopus: 2-s2.0-85186919082
Elibrary: 82134673
Citing:
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Web of science 1
Scopus 1
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