We investigate the influence of the shape parameter in the meshless Gaussian RBF finite difference method with irregular centres on the quality of the approximation of the Dirichlet problem for the Poisson equation with smooth solution. Numerical experiments show that the optimal shape parameter strongly depends on the problem, but insignificantly on the density of the centres. Therefore, we suggest a multilevel algorithm that effectively finds near-optimal shape parameter, which helps to significantly reduce the error. Comparison to the finite element method and to the generalised finite differences obtained in the flat limits of the Gaussian RBF is provided
Radial basis function generated finite difference (RBF-FD) approximations generalize grid-based regu...
Recent research into using the Method of Approximate Particular Solutions to numerically solve parti...
Abstract Many radial basis function (RBF) methods contain a free shape parameter that plays an impor...
AbstractWe investigate the influence of the shape parameter in the meshless Gaussian radial basis fu...
Radial basis functions (RBFs) have become a popular method for interpolation and solution of partial...
Radial basis functions (RBFs) have become a popular method for the solution of partial differential ...
We consider adaptive meshless discretisation of the Dirichlet problem for Poisson equation based on ...
Abstract. Traditional finite difference (FD) methods are designed to be exact for low degree polynom...
Radial basis function (RBF) has been widely used in many scientific computing and engineering applic...
AbstractThis is the fifth of our series of works about the shape parameter. We now explore the param...
The Radial Basis Function (RBF) method has been considered an important meshfree tool for numerical ...
The solution of the Helmholtz equation is a fundamental step in frequency domain seismic imaging. Th...
In this paper, we totally discard the traditional trial-and-error algorithms of choosing the accepta...
In this paper, we investigate the use of radial basis functions for solving Poisson problems with a ...
This paper presents the combination of new mesh-free radial basis function network (RBFN) methods an...
Radial basis function generated finite difference (RBF-FD) approximations generalize grid-based regu...
Recent research into using the Method of Approximate Particular Solutions to numerically solve parti...
Abstract Many radial basis function (RBF) methods contain a free shape parameter that plays an impor...
AbstractWe investigate the influence of the shape parameter in the meshless Gaussian radial basis fu...
Radial basis functions (RBFs) have become a popular method for interpolation and solution of partial...
Radial basis functions (RBFs) have become a popular method for the solution of partial differential ...
We consider adaptive meshless discretisation of the Dirichlet problem for Poisson equation based on ...
Abstract. Traditional finite difference (FD) methods are designed to be exact for low degree polynom...
Radial basis function (RBF) has been widely used in many scientific computing and engineering applic...
AbstractThis is the fifth of our series of works about the shape parameter. We now explore the param...
The Radial Basis Function (RBF) method has been considered an important meshfree tool for numerical ...
The solution of the Helmholtz equation is a fundamental step in frequency domain seismic imaging. Th...
In this paper, we totally discard the traditional trial-and-error algorithms of choosing the accepta...
In this paper, we investigate the use of radial basis functions for solving Poisson problems with a ...
This paper presents the combination of new mesh-free radial basis function network (RBFN) methods an...
Radial basis function generated finite difference (RBF-FD) approximations generalize grid-based regu...
Recent research into using the Method of Approximate Particular Solutions to numerically solve parti...
Abstract Many radial basis function (RBF) methods contain a free shape parameter that plays an impor...