Abstract. The radial basis function interpolant is known to be the best approximation to a set of scattered data when the error is measured in the native space norm. The approximate moving least squares method, on the other hand, was recently proposed as an efficient approximation method that avoids the solution of the system of linear equations associated with the radial basis function interpolant. In this paper we propose and analyze an algorithm that iterates on the residuals of an approximate moving least squares approximation. We show that this algorithm yields the radial basis interpolant in the limit. Supporting numerical experiments are also included. Key words: ��Author please supply��
The combination of polyharmonic splines (PHS) with high degree polynomials (PHS+poly) has recently o...
This paper reformulates the moving least square interpolation scheme in a framework of the so-called...
Interpolation or approximation of scattered data is very often task in engineering problems. The Rad...
Abstract. We propose a fast and accurate approximation method for large sets of multivariate data us...
Abstract. We describe two experiments recently conducted with the approximate moving least squares (...
We propose a fast and accurate approximation method for large sets of multivariate data using radia...
For multivariate problems with many scattered data locations the use of radial functions has proven ...
AbstractGiven a function f in scattered data points x1,…,xn ∈ RS we solve the least squares problem ...
We introduce moving least squares approximation as an approximation scheme on the sphere. We prove e...
Abstract: Owing to the meshless and local character-istics, moving least squares (MLS) methods have ...
AbstractIt is a common procedure for scattered data approximation to use local polynomial fitting in...
An efficient and robust algorithm and aMatlab code ratdisk are presented for rational interpolation ...
AbstractMoving least-squares methods for interpolation or approximation of scattered data are well k...
An efficient and robust algorithm and a Matlab code ratdisk are presented for rational interpolation...
. We investigate adaptive least squares approximation to scattered data given over the surface of th...
The combination of polyharmonic splines (PHS) with high degree polynomials (PHS+poly) has recently o...
This paper reformulates the moving least square interpolation scheme in a framework of the so-called...
Interpolation or approximation of scattered data is very often task in engineering problems. The Rad...
Abstract. We propose a fast and accurate approximation method for large sets of multivariate data us...
Abstract. We describe two experiments recently conducted with the approximate moving least squares (...
We propose a fast and accurate approximation method for large sets of multivariate data using radia...
For multivariate problems with many scattered data locations the use of radial functions has proven ...
AbstractGiven a function f in scattered data points x1,…,xn ∈ RS we solve the least squares problem ...
We introduce moving least squares approximation as an approximation scheme on the sphere. We prove e...
Abstract: Owing to the meshless and local character-istics, moving least squares (MLS) methods have ...
AbstractIt is a common procedure for scattered data approximation to use local polynomial fitting in...
An efficient and robust algorithm and aMatlab code ratdisk are presented for rational interpolation ...
AbstractMoving least-squares methods for interpolation or approximation of scattered data are well k...
An efficient and robust algorithm and a Matlab code ratdisk are presented for rational interpolation...
. We investigate adaptive least squares approximation to scattered data given over the surface of th...
The combination of polyharmonic splines (PHS) with high degree polynomials (PHS+poly) has recently o...
This paper reformulates the moving least square interpolation scheme in a framework of the so-called...
Interpolation or approximation of scattered data is very often task in engineering problems. The Rad...