Numerical differentiation by radial basis functions approximation |
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Authors: | T. Wei Y. C. Hon |
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Affiliation: | (1) School of Mathematics and Statistics, Lanzhou University, Lanzhou, China;(2) Department of Mathematics, City University of Hong Kong, Hong Kong, China |
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Abstract: | Based on radial basis functions approximation, we develop in this paper a new com-putational algorithm for numerical differentiation. Under an a priori and an a posteriori choice rules for the regularization parameter, we also give a proof on the convergence error estimate in reconstructing the unknown partial derivatives from scattered noisy data in multi-dimension. Numerical examples verify that the proposed regularization strategy with the a posteriori choice rule is effective and stable to solve the numerical differential problem. *The work described in this paper was partially supported by a grant from CityU (Project No. 7001646) and partially supported by the National Natural Science Foundation of China (No. 10571079). |
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Keywords: | numerical differentiation radial basis functions Tikhonov regularization |
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