Numerical derivatives from one-dimensional scattered noisy data

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)171-179
Journal / PublicationJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 1 Jan 2005


Based on the cubic spline theory, we propose in this paper a regularization method for reconstructing numerical differentiation from one-dimensional scattered noisy data. Under two different choice rules for a suitable regularization parameter, the regularized solutions can be derived. Convergence results for the approximate derivative are given. Numerical experiments verify that the proposed strategy with the Morozov's discrepancy principle for the choice of regularization parameter is effective and stable. © 2005 IOP Publishing Ltd.