Convergence rates for multivariate smoothing spline functions
Journal of Approximation Theory
Almost sure convergence of smoothing Dm-splines for noisy data
Numerische Mathematik
Approximation order of bivariate spline interpolation for arbitrary smoothness
Journal of Computational and Applied Mathematics
Piecewise Quadratic Approximations on Triangles
ACM Transactions on Mathematical Software (TOMS)
Minimal energy Cr-surfaces on uniform Powell-Sabin type meshes
Mathematics and Computers in Simulation
Filling polygonal holes with minimal energy surfaces on Powell-Sabin type triangulations
Journal of Computational and Applied Mathematics
Mathematics and Computers in Simulation
Mathematics and Computers in Simulation
Multiresolution analysis for minimal energy Cr-surfaces on Powell-Sabin type meshes
MMCS'08 Proceedings of the 7th international conference on Mathematical Methods for Curves and Surfaces
Hi-index | 7.29 |
In this paper we present a method to obtain for noisy data, a C^r-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.