Efficient computation with radial basis functions

Lead Research Organisation: University of Leicester
Department Name: Mathematics

Abstract

The proposal is concerned with developing more effective computational techniques for the reconstruction of information when the data has little structure and may be in high space dimension.Radial basis function (RBF) methods have proved a popular choice for this task. We intend to continue the development of cheap preconditioning methods for RBFs and provide theory and numerical experiments to support efficient computational methods for reconstruction when data is anisotropic.

Publications

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Beatson R (2010) Error bounds for anisotropic RBF interpolation in Journal of Approximation Theory

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Beatson R (2011) Better bases for radial basis function interpolation problems in Journal of Computational and Applied Mathematics

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Li B (2011) Approximation Algorithms for Complex Systems - Proceedings of the 6th International Conference on Algorithms for Approximation, Ambleside, UK, 31st August - 4th September 2009

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N/a Beatson (2009) Adaptive data fitting with anisotropic radial basis functions in n/a in Final Report Data