The behavior of two different types of basis functions for the meshless Radial Point Interpolation Method (RPIM) is investigated in this paper. A 2D test function is interpolated through Gaussian and Wendland basis functions and the approximation errors on the low-order derivatives of the test function are calculated. It is shown that the Gaussian basis function is more appropriate for the interpolation in small support domains where as Wendland basis function is more accurate for larger support domains.Zahra Shaterian, Thomas Kaufmann and Christophe Fumeau
AbstractMultivariate interpolation of smooth data using smooth radial basis functions is considered....
This paper compares radial basis function interpolants on different spaces. The spaces are generated...
AbstractWe introduce a class of matrix-valued radial basis functions (RBFs) of compact support that ...
A traditional criterion to calculate the numerical stability of the interpolation matrix is its stan...
In order to overcome the possible singularity associated with the Point Interpolation Method (PIM), ...
The radial basis function (RBF), also known as the Radial Point Interpolation Method (RPIM), is a me...
We suggest an improvement of Wu-Schaback local error bound for radial basis interpolation by using a...
In this article, an enriched radial point interpolation method (e-RPIM) is developed for computation...
In this work the advances in meshfree methods, partic- ularly the Radial Basis Function based meshfr...
Abstract. Radial basis function interpolation refers to a method of interpolation which writes the i...
In this thesis we are concerned with the approximation of functions by radial basis function interpo...
10.1002/nme.489International Journal for Numerical Methods in Engineering54111623-1648IJNM
AbstractThis paper presents a truly meshfree method referred to as radial point interpolation colloc...
This paper compares two different approaches for the time-domain meshless Radial Point Interpolation...
In this paper we propose a rescaled localized radial basis function (RL-RBF) interpolation method, b...
AbstractMultivariate interpolation of smooth data using smooth radial basis functions is considered....
This paper compares radial basis function interpolants on different spaces. The spaces are generated...
AbstractWe introduce a class of matrix-valued radial basis functions (RBFs) of compact support that ...
A traditional criterion to calculate the numerical stability of the interpolation matrix is its stan...
In order to overcome the possible singularity associated with the Point Interpolation Method (PIM), ...
The radial basis function (RBF), also known as the Radial Point Interpolation Method (RPIM), is a me...
We suggest an improvement of Wu-Schaback local error bound for radial basis interpolation by using a...
In this article, an enriched radial point interpolation method (e-RPIM) is developed for computation...
In this work the advances in meshfree methods, partic- ularly the Radial Basis Function based meshfr...
Abstract. Radial basis function interpolation refers to a method of interpolation which writes the i...
In this thesis we are concerned with the approximation of functions by radial basis function interpo...
10.1002/nme.489International Journal for Numerical Methods in Engineering54111623-1648IJNM
AbstractThis paper presents a truly meshfree method referred to as radial point interpolation colloc...
This paper compares two different approaches for the time-domain meshless Radial Point Interpolation...
In this paper we propose a rescaled localized radial basis function (RL-RBF) interpolation method, b...
AbstractMultivariate interpolation of smooth data using smooth radial basis functions is considered....
This paper compares radial basis function interpolants on different spaces. The spaces are generated...
AbstractWe introduce a class of matrix-valued radial basis functions (RBFs) of compact support that ...