Radial basis functions are well-known and successful tools for the interpolation of data in many dimensions. Several radial basis functions of compact support that give rise to nonsingular interpolation problems have been proposed, and in this paper we study a new, larger class of smooth radial functions of compact support which contains other compactly supported ones that were proposed earlier...

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...

Regularization with radial basis functions is an effective method in many machine learning applications. In recent years classes of radial basis functions with compact support have been proposed in the approximation theory literature and have become more and more popular due to their computational advantages. In this paper we study the statistical properties of the method of regularization with...

we compare performance of adaptive schemes which are based on radial-basis functions and kalman filters for fast extraction of auditory evoked potentials. moreover, we propose a new method based on evoked potential modeling in the kalman filter framework, which can improve the accuracy compared to the existing methods. simulation results show that adaptive schemes and the kalman method are not ...

We introduce a class of matrix-valued radial basis functions (RBFs) of compact support that can be customized, e.g. chosen to be divergence-free. We then derive and discuss error estimates for interpolants and derivatives based on these matrixvalued RBFs.

Approximation and Interpolation Employing Divergence–free Radial Basis Functions with Applications. (May 2002) Svenja Lowitzsch, Dipl., Georg-August University, Göttingen Co–Chairs of Advisory Committee: Dr. Francis J. Narcowich Dr. Joseph D. Ward Approximation and interpolation employing radial basis functions has found important applications since the early 1980’s in areas such as signal proc...

Common elastic registration schemes based on landmarks and radial basis functions (RBFs) such as thin-plate splines or multiquadrics are global. Here, we introduce radial basis functions with compact support for elastic registration of medical images which have an improved locality, i.e. which allow to constrain elastic deformations to image parts where required. We give the theoretical backgro...