Legendre superconvergent Galerkin-collocation type methods for Hammerstein equations

Autor:	Driss Sbibih, M. Tahrichi, C. Allouch
Rok vydání:	2019
Předmět:	Computational Mathematics Collocation Rate of convergence Kernel (image processing) Applied Mathematics Orthographic projection Applied mathematics Superconvergence Galerkin method Legendre polynomials Projection (linear algebra) Mathematics::Numerical Analysis Mathematics
Zdroj:	Journal of Computational and Applied Mathematics. 353:253-264
ISSN:	0377-0427
DOI:	10.1016/j.cam.2018.12.040
Popis:	In this paper, polynomially based superconvergent projection methods for approximating the solution of Hammerstein equations with a smooth kernel are studied. The projection is chosen to be either the orthogonal projection or an interpolatory projection using Legendre polynomial bases. The paper is motivated by the results reported in Nelakanti and Mandal (2017)[19]. The order of convergence of the proposed methods and those of superconvergence of the iterated versions are analyzed. Numerical example is given to illustrate the theoretical results.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::37c39ab813ef80539030f6ab12370e3c https://doi.org/10.1016/j.cam.2018.12.040 Zobrazit plný text záznamu Full Text from ScienceDirect