The partition of unity (PU) method, performed with local radial basis function (RBF) approximants, has been proved to be an effective tool for solving large scattered data interpolation problems. However, in order to achieve a good accuracy, the question about how many points we have to consider on each local subdomain, i.e. how large can be the local data sets, needs to be answered. Moreover, it is well-known that also the shape parameter affects the accuracy of the local RBF approximants and, as a consequence, of the PU interpolant. Thus here, both the shape parameter used to fit the local problems and the size of the associated linear systems are supposed to vary among the subdomains. They are selected by minimizing an a priori error estimate. As evident from extensive numerical experiments and applications provided in the paper, the proposed method turns out to be extremely accurate also when data with non-homogeneous density are considered.

Optimal Selection of Local Approximants in RBF-PU Interpolation

CAVORETTO, Roberto;DE ROSSI, Alessandra;PERRACCHIONE, EMMA
2018-01-01

Abstract

The partition of unity (PU) method, performed with local radial basis function (RBF) approximants, has been proved to be an effective tool for solving large scattered data interpolation problems. However, in order to achieve a good accuracy, the question about how many points we have to consider on each local subdomain, i.e. how large can be the local data sets, needs to be answered. Moreover, it is well-known that also the shape parameter affects the accuracy of the local RBF approximants and, as a consequence, of the PU interpolant. Thus here, both the shape parameter used to fit the local problems and the size of the associated linear systems are supposed to vary among the subdomains. They are selected by minimizing an a priori error estimate. As evident from extensive numerical experiments and applications provided in the paper, the proposed method turns out to be extremely accurate also when data with non-homogeneous density are considered.
2018
74
1
22
https://arxiv.org/pdf/1703.04282
https://arxiv.org/abs/1703.04282
Cross-validation; Meshfree approximation; Partition of unity method; Radial basis functions; Scattered data interpolation; Searching procedures
Cavoretto, Roberto; De Rossi, Alessandra; Perracchione, Emma
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1633650
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