Abstract
Radial Basis Function (RBF) methods are important tools for scattered data interpolation and for the solution of Partial Differential Equations in complexly shaped domains. The most straight forward approach used to evaluate the methods involves solving a linear system which is typically poorly conditioned. The Matlab Radial Basis Function toolbox features a regularization method for the ill-conditioned system, extended precision floating point arithmetic, and symmetry exploitation for the purpose of reducing flop counts of the associated numerical linear algebra algorithms.
DOI: https://doi.org/10.5334/jors.131 | Journal eISSN: 2049-9647
Language: English
Submitted on: May 28, 2016
Accepted on: Jan 13, 2017
Published on: Mar 27, 2017
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
© 2017 Scott A. Sarra, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.
