In the recent paper 1, a new method to compute stable kernel-based
interpolants has been presented. This rescaled interpolation method
combines the standard kernel interpolation with a properly defined
rescaling operation, which smooths the oscillations of the interpolant.
Although promising, this procedure lacks a systematic theoretical
investigation. Through our analysis, this novel method can be understood
as standard kernel interpolation by means of a properly rescaled
kernel. This point of view allows us to consider its error and stability
properties.
%0 Book Section
%1 demarchi2017rescaled
%A De Marchi, Stefano
%A Idda, Andrea
%A Santin, Gabriele
%B Approximation Theory XV: San Antonio 2016
%C Cham
%D 2017
%E Fasshauer, Gregory E.
%E Schumaker, Larry L.
%I Springer International Publishing
%K imported vorlaeufig
%P 39--59
%R 10.1007/978-3-319-59912-0_3
%T A Rescaled Method for RBF Approximation
%U https://doi.org/10.1007/978-3-319-59912-0_3
%X In the recent paper 1, a new method to compute stable kernel-based
interpolants has been presented. This rescaled interpolation method
combines the standard kernel interpolation with a properly defined
rescaling operation, which smooths the oscillations of the interpolant.
Although promising, this procedure lacks a systematic theoretical
investigation. Through our analysis, this novel method can be understood
as standard kernel interpolation by means of a properly rescaled
kernel. This point of view allows us to consider its error and stability
properties.
%@ 978-3-319-59912-0
@inbook{demarchi2017rescaled,
abstract = {In the recent paper [1], a new method to compute stable kernel-based
interpolants has been presented. This rescaled interpolation method
combines the standard kernel interpolation with a properly defined
rescaling operation, which smooths the oscillations of the interpolant.
Although promising, this procedure lacks a systematic theoretical
investigation. Through our analysis, this novel method can be understood
as standard kernel interpolation by means of a properly rescaled
kernel. This point of view allows us to consider its error and stability
properties.},
added-at = {2018-07-20T10:54:15.000+0200},
address = {Cham},
author = {De Marchi, Stefano and Idda, Andrea and Santin, Gabriele},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2457ee4d0e4349fe956682f44cc20759f/mhartmann},
booktitle = {Approximation Theory XV: San Antonio 2016},
doi = {10.1007/978-3-319-59912-0_3},
editor = {Fasshauer, Gregory E. and Schumaker, Larry L.},
interhash = {f31e4e68f9384a84cbddbdf77cbc5ea6},
intrahash = {457ee4d0e4349fe956682f44cc20759f},
isbn = {978-3-319-59912-0},
keywords = {imported vorlaeufig},
owner = {santinge},
pages = {39--59},
publisher = {Springer International Publishing},
timestamp = {2018-07-20T08:54:15.000+0200},
title = {A Rescaled Method for {RBF} Approximation},
url = {https://doi.org/10.1007/978-3-319-59912-0_3},
year = 2017
}