ScholarLens Back to search
2020•Unpublished venueRequires access

Behavioral Study of Various Radial Basis Functions for Approximation and Interpolation Purposes

Martin Červenka, Václav Skala

Open publisher page 7 citations

Abstract

Both approximation and interpolation are techniques commonly used in many scientific areas. Many approaches are depending on input data type, result purpose etc. Input data can be formed in a mesh or not (meshless/meshfree data).This contribution is oriented on meshless data approximation and interpolation using Radial Basis Functions (RBFs). Different RBFs behaves differently, but many of them have a shape parameter. This paper compares various RBFs concerning its shape parameters and provides some experimental results for each of the selected RBF.

About this research paper

What this paper is about

Both approximation and interpolation are techniques commonly used in many scientific areas. Many approaches are depending on input data type, result purpose etc. Input data can be formed in a mesh or not (meshless/meshfree data).This contribution is oriented on meshless data approximation and interpolation using Radial Basis Functions (RBFs). Different RBFs behaves differently, but many of them have a shape parameter. This paper compares various RBFs concerning its shape parameters and provides some experimental results for each of the selected RBF.

Why it matters

OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Both approximation and interpolation are techniques commonly used in many scientific areas. Many approaches are depending on input data type, result purpose etc. Input data can be formed in a mesh or not (meshless/meshfree data).This contribution is oriented on meshless data approximation and interpolation using Radial Basis Functions (RBFs). Different RBFs behaves differently, but many of them have a shape parameter. This paper compares various RBFs concerning its shape parameters and provides some experimental results for each of the selected RBF.

Key concepts: Radial basis function, Interpolation (computer graphics), Meshfree methods, Computer science, Hierarchical RBF, Basis (linear algebra), Shape parameter, Applied mathematics

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
Behavioral Study of Various Radial Basis Functions for Approximation and Interpolation Purposes — Research Paper | ScholarLens