1 Radial Basis Functions 2 1.1 Multivariate Interpolation and Positive Definiteness . . . . . . 3 1.2 Stability and Scaling . . . . . . . . . . . . . . . . . . . . . . . 5 1.3 Solving Partial Differential Equations . . . . . . . . . . . . . . 7 1.4 Comparison of Strong and Weak Problems . . . . . . . . . . . 8 1.5 Collocation Techniques . . . . . . . . . . . . . . . . . . . . . . 10 1.6 Method ...

In many cases, multivariate interpolation by smooth radial basis functions converges towards polynomial interpolants, when the basis functions are scaled to become “wide”. In particular, examples show that interpolation by scaled Gaussians seems to converge towards the de Boor/Ron “least” polynomial interpolant. The paper starts by providing sufficient criteria for the convergence of radial int...

The recently proposed domain-free discretization (DFD) method is based on the Lagrange interpolation and polynomial-based differential quadrature (PDQ) method. In this article, the radial basis function (RBF) approximation is used in the DFD method as the interpolation scheme for function approximation, and the RBF-DQ method is applied to derivative approximation. The new variant of DFD method ...

In this paper, An effective and simple numerical method is proposed for solving systems of integral equations using radial basis functions (RBFs). We present an algorithm based on interpolation by radial basis functions including multiquadratics (MQs), using Legendre-Gauss-Lobatto nodes and weights. Also a theorem is proved for convergence of the algorithm. Some numerical examples are presented...

In this paper, a numerical method is proposed for solving optimal control problem of Volterra integral equations using radial basis functions (RBFs) for approximating unknown function. Actually, the method is based on interpolation by radial basis functions including multiquadrics (MQs), to determine the control vector and the corresponding state vector in linear dynamic system while minimizing...

A meshfree computational method is proposed in this paper to solve Kirchhoff plate problems of various geometries. The deflection of the thin plate is approximated by using a Hermite-type radial basis function approximation technique. The standard Galerkin method is adopted to discretize the governing partial differential equations which were derived from using the Kirchhoff’s plate theory. The...

Having various concrete industrial applications in mind we focus on surface fitting to large scattered data sets. We describe a general method for modelling data which incorporates both filtering using triangulations, and hierarchical interpolation based on compactly supported radial basis functions. The uniformity of the data points plays a significant role. The utility of the method is confir...

A radial basis function implementation of the meshless local Petrov-Galerkin (MLPG) method is presented to study Euler-Bernoulli beam problems. Radial basis functions, rather than generalized moving least squares (GMLS) interpolations, are used to develop the trial functions. This choice yields a computationally simpler method as fewer matrix inversions and multiplications are required than whe...