We consider error estimates for interpolation by a special class of compactly supported radial basis functions. These functions consist of a univariate polynomial within their support and are of minimal degree depending on space dimension and smoothness. Their associated ``native'' Hilbert spaces ar
On Power Functions and Error Estimates for Radial Basis Function Interpolation
β Scribed by Will Light; Henry Wayne
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 431 KB
- Volume
- 92
- Category
- Article
- ISSN
- 0021-9045
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β¦ Synopsis
This paper discusses approximation errors for interpolation in a variational setting which may be obtained from the analysis given by Golomb and Weinberger. We show how this analysis may be used to derive the power function estimate of the error as introduced by Schaback and Powell. A simple error tool for the power function is presented, which is similar to one appearing in the work of Madych and Nelson. It is then shown that this tool is adequate to reproducing the original error analysis presented by Duchon. An interesting consequence of our work is that no explicit use is made of the polynomial reproduction properties of the interpolation operator.
π SIMILAR VOLUMES
Radial basis function interpolation has attracted a lot of interest in recent years. For popular choices, for example thin plate splines, this problem has a variational formulation, i.e. the interpolant minimizes a semi-norm on a certain space of radial functions. This gives rise to a function space
## Abstract A point interpolation meshless method is proposed based on combining radial and polynomial basis functions. Involvement of radial basis functions overcomes possible singularity associated with the meshless methods based on only the polynomial basis. This nonβsingularity is useful in con