Add to ORKGWe introduce moving least squares approximation as an approximation scheme on the sphere. We prove error estimates and approximation orders. Finally, we show certain numerical results
Numerical methods may require derivatives of functions whose values are known only on irregularly sp...
The concise review systematically summarises the state-of-the-art variants of Moving Least Squares (...
We investigate the uniform approximation provided by least squares polynomials on the unit Euclidean...
Abstract. We describe two experiments recently conducted with the approximate moving least squares (...
Abstract. The radial basis function interpolant is known to be the best approximation to a set of sc...
AbstractIt is a common procedure for scattered data approximation to use local polynomial fitting in...
Local polynomial reproduction is a key ingredient in providing error estimates for several approxima...
Abstract. We propose a fast and accurate approximation method for large sets of multivariate data us...
Abstract: Owing to the meshless and local character-istics, moving least squares (MLS) methods have ...
AbstractMoving least-square (MLS) is an approximation method for data interpolation, numerical analy...
For multivariate problems with many scattered data locations the use of radial functions has proven ...
. We investigate adaptive least squares approximation to scattered data given over the surface of th...
We propose a fast and accurate approximation method for large sets of multivariate data using radia...
We consider polynomial approximation on the unit sphere S² = {(x, y, z) ∈ R³ :x² + y² + z² = 1} by a...
This paper is aimed at introducing the concept of Spherical Interpolating Moving Least Squares to th...
Numerical methods may require derivatives of functions whose values are known only on irregularly sp...
The concise review systematically summarises the state-of-the-art variants of Moving Least Squares (...
We investigate the uniform approximation provided by least squares polynomials on the unit Euclidean...
Abstract. We describe two experiments recently conducted with the approximate moving least squares (...
Abstract. The radial basis function interpolant is known to be the best approximation to a set of sc...
AbstractIt is a common procedure for scattered data approximation to use local polynomial fitting in...
Local polynomial reproduction is a key ingredient in providing error estimates for several approxima...
Abstract. We propose a fast and accurate approximation method for large sets of multivariate data us...
Abstract: Owing to the meshless and local character-istics, moving least squares (MLS) methods have ...
AbstractMoving least-square (MLS) is an approximation method for data interpolation, numerical analy...
For multivariate problems with many scattered data locations the use of radial functions has proven ...
. We investigate adaptive least squares approximation to scattered data given over the surface of th...
We propose a fast and accurate approximation method for large sets of multivariate data using radia...
We consider polynomial approximation on the unit sphere S² = {(x, y, z) ∈ R³ :x² + y² + z² = 1} by a...
This paper is aimed at introducing the concept of Spherical Interpolating Moving Least Squares to th...
Numerical methods may require derivatives of functions whose values are known only on irregularly sp...
The concise review systematically summarises the state-of-the-art variants of Moving Least Squares (...
We investigate the uniform approximation provided by least squares polynomials on the unit Euclidean...