Author: Smolik, Michal; Skala, Vaclav
Title: Efficient Speed-Up of Radial Basis Functions Approximation and Interpolation Formula Evaluation Cord-id: atgf4uki Document date: 2020_8_24
ID: atgf4uki
Snippet: This paper presents a method for efficient Radial basis function (RBF) evaluation if compactly supported radial basis functions (CSRBF) are used. Application of CSRBF leads to sparse matrices, due to limited influence of radial basis functions in the data domain and thus non-zero weights (coefficients) are valid only for some areas in the data domain. The presented algorithm uses space subdivision which enables us to use only relevant weights for efficient RBF function evaluation. This approach
Document: This paper presents a method for efficient Radial basis function (RBF) evaluation if compactly supported radial basis functions (CSRBF) are used. Application of CSRBF leads to sparse matrices, due to limited influence of radial basis functions in the data domain and thus non-zero weights (coefficients) are valid only for some areas in the data domain. The presented algorithm uses space subdivision which enables us to use only relevant weights for efficient RBF function evaluation. This approach is applicable for 2D and 3D case and leads to a significant speed-up. This approach is applicable in cases when the RBF function is evaluated repeatably.
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