New RBF collocation methods and kernel RBF with applications

Fuente: arXiv
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Main Author: Chen, W.
Format: Preprint
Published: 2001
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_version_ 1866915559857192960
author Chen, W.
author_facet Chen, W.
contents A few novel radial basis function (RBF) discretization schemes for partial differential equations are developed in this study. For boundary-type methods, we derive the indirect and direct symmetric boundary knot methods. Based on the multiple reciprocity principle, the boundary particle method is introduced for general inhomogeneous problems without using inner nodes. For domain-type schemes, by using the Green integral we develop a novel Hermite RBF scheme called the modified Kansa method, which significantly reduces calculation errors at close-to-boundary nodes. To avoid Gibbs phenomenon, we present the least square RBF collocation scheme. Finally, five types of the kernel RBF are also briefly presented.
format Preprint
id arxiv_https___arxiv_org_abs_cs_0111063
institution arXiv
publishDate 2001
record_format arxiv
spellingShingle New RBF collocation methods and kernel RBF with applications
Chen, W.
Numerical Analysis
Computational Engineering, Finance, and Science
G1.3, G1.8
A few novel radial basis function (RBF) discretization schemes for partial differential equations are developed in this study. For boundary-type methods, we derive the indirect and direct symmetric boundary knot methods. Based on the multiple reciprocity principle, the boundary particle method is introduced for general inhomogeneous problems without using inner nodes. For domain-type schemes, by using the Green integral we develop a novel Hermite RBF scheme called the modified Kansa method, which significantly reduces calculation errors at close-to-boundary nodes. To avoid Gibbs phenomenon, we present the least square RBF collocation scheme. Finally, five types of the kernel RBF are also briefly presented.
title New RBF collocation methods and kernel RBF with applications
topic Numerical Analysis
Computational Engineering, Finance, and Science
G1.3, G1.8
url https://arxiv.org/abs/cs/0111063