Abstract
The approximation of scattered data is known technique in computer science. We propose a new strategy for the placement of radial basis functions respecting points of inflection. The placement of radial basis functions has a great impact on the approximation quality. Due to this fact we propose a new strategy for the placement of radial basis functions with respect to the properties of approximated function, including the extreme and the inflection points. Our experimental results proved high quality of the proposed approach and high quality of the final approximation.
The research was supported by projects Czech Science Foundation (GACR) No. 17-05534S and partially by SGS 2019-016.
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Acknowledgments
The authors would like to thank their colleagues at the University of West Bohemia, Plzen, for their discussions and suggestions, and anonymous reviewers for their valuable comments and hints provided. The research was supported by projects Czech Science Foundation (GACR) No. 17-05534S and partially by SGS 2019-016.
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Cervenka, M., Smolik, M., Skala, V. (2019). A New Strategy for Scattered Data Approximation Using Radial Basis Functions Respecting Points of Inflection. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11619. Springer, Cham. https://doi.org/10.1007/978-3-030-24289-3_24
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