Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4642100 | Journal of Computational and Applied Mathematics | 2008 | 11 Pages |
Abstract
In this paper we present a method to obtain for noisy data, a Cr-surface, for any r⩾1, on a polygonal domain which approximates a Lagrangian data set and minimizes a quadratic functional that contains some terms associated with Sobolev semi-norms weighted by some smoothing parameters. The minimization space is composed of bivariate spline functions constructed on a uniform Powell-Sabin-type triangulation of the domain. We prove a result of almost sure convergence and we choose optimal values of the smoothing parameters by adapting the generalized cross-validation method. We finish with some numerical and graphical examples.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
D. Barrera, M.A. Fortes, P. González, M. Pasadas,