RT Journal Article
T1 Comparison of moving least squares and RBF+poly for interpolation and derivative approximation
A1 Bayona Revilla, Víctor
AB The combination of polyharmonic splines (PHS) with high degree polynomials (PHS+poly) has recently opened new opportunities for radial basis function generated finite difference approximations. The PHS+poly formulation, which relies on a polynomial least squares fitting to enforce the local polynomial reproduction property, resembles somehow the so-called moving least squares (MLS) method. Although these two meshfree approaches are increasingly used nowadays, no direct comparison has been done yet. The present study aims to fill this gap, focusing on scattered data interpolation and derivative approximation. We first review the MLS approach and show that under some mild assumptions PHS+poly can be formulated analogously. Based on heuristic perspectives and numerical demonstrations, we then compare their performances in 1-D and 2-D. One key result is that, as previously found for PHS+poly, MLS can also overcome the edge oscillations (Runge's phenomenon) by simply increasing the stencil size for a fixed polynomial degree. This is, however, controlled by a weighted least squares fitting which fails for high polynomial degrees. Overall, PHS+poly is found to perform superior in terms of accuracy and robustness
PB Springer
SN 0885-7474
YR 2019
FD 2019-10-01
LK https://hdl.handle.net/10016/31955
UL https://hdl.handle.net/10016/31955
LA eng
NO The author would like to thank Bengt Fornberg, who took the time to carefully review this manuscript and make useful comments. This work was supported by Spanish MECD Grant FIS2016-77892-R.
DS e-Archivo
RD 17 jul. 2024