Adaptive greedy techniques for approximate solution of large RBF systems
type: Item
instance of: scholarly article
title: Adaptive greedy techniques for approximate solution of large RBF systems
zbMATH Open document ID: 0957.65021
DOI: 10.1023/A:1019105612985
author: Robert Schaback
author: Holger Wendland
published in: Numerical Algorithms
publication date: 2000-11-22T00:00:00Z
review text: An iterative method is proposed for solving large sparse linear systems arizing from interpolation problems using compactly supported radial basis functions (RBFs). Small subsets of the interpolation points are selected and the current approximative solution is refined. Convergence rate is linear. The method can be generalized to positive definite linear systems.
Mathematics Subject Classification ID: 65F10
Mathematics Subject Classification ID: 65F50
Mathematics Subject Classification ID: 65D05
zbMATH DE Number: 1534772
zbMATH Keywords: adaptive greedy techniques
zbMATH Keywords: convergence
zbMATH Keywords: iterative method
zbMATH Keywords: large sparse linear systems
zbMATH Keywords: interpolation
zbMATH Keywords: radial basis functions
reviewed by: F. Szidarovszky
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 1534772