Regular Families of Kernels for Nonlinear Approximation
Functional Analysis
2019-03-15 v3 Classical Analysis and ODEs
Abstract
This article studies sufficient conditions on families of approximating kernels which provide --term approximation errors from an associated nonlinear approximation space which match the best known orders of --term wavelet expansion. These conditions provide a framework which encompasses some notable approximation kernels including splines, so-called cardinal functions, and many radial basis functions such as the Gaussians and general multiquadrics. Examples of such kernels are given to justify the criteria, and some computational experiments are done to demonstrate the theoretical results. Additionally, the techniques involved allow for some new results on --term interpolation of Sobolev functions via radial basis functions.
Cite
@article{arxiv.1606.06676,
title = {Regular Families of Kernels for Nonlinear Approximation},
author = {Keaton Hamm and Jeff Ledford},
journal= {arXiv preprint arXiv:1606.06676},
year = {2019}
}