Multivariate spline spaces

Author(s):  
Ren-Hong Wang
Keyword(s):  
2021 ◽  
Vol 15 ◽  
pp. 174830262110084
Author(s):  
Bishnu P Lamichhane ◽  
Elizabeth Harris ◽  
Quoc Thong Le Gia

We compare a recently proposed multivariate spline based on mixed partial derivatives with two other standard splines for the scattered data smoothing problem. The splines are defined as the minimiser of a penalised least squares functional. The penalties are based on partial differential operators, and are integrated using the finite element method. We compare three methods to two problems: to remove the mixture of Gaussian and impulsive noise from an image, and to recover a continuous function from a set of noisy observations.


Acta Numerica ◽  
1993 ◽  
Vol 2 ◽  
pp. 65-109 ◽  
Author(s):  
C. de Boor

This article was supposed to be on ‘multivariate splines». An informal survey, taken recently by asking various people in Approximation Theory what they consider to be a ‘multivariate spline’, resulted in the answer that a multivariate spline is a possibly smooth piecewise polynomial function of several arguments. In particular the potentially very useful thin-plate spline was thought to belong more to the subject of radial basis funtions than in the present article. This is all the more surprising to me since I am convinced that the variational approach to splines will play a much greater role in multivariate spline theory than it did or should have in the univariate theory. Still, as there is more than enough material for a survey of multivariate piecewise polynomials, this article is restricted to this topic, as is indicated by the (changed) title.


Author(s):  
Wolfgang Dahmen ◽  
Charles A. Micchelli

AbstractIn this paper, we determine the optimal controlled approximation rates from certain bivariate splines on regular meshes.


2014 ◽  
Vol 265 ◽  
pp. 276-289 ◽  
Author(s):  
Ren-Hong Wang ◽  
Qing-Jie Guo ◽  
Chun-Gang Zhu ◽  
Chun-Jing Li

2007 ◽  
Vol 54 (3) ◽  
pp. 415-426 ◽  
Author(s):  
Ren-Hong Wang ◽  
Feng-Gong Lang

2001 ◽  
Vol 111 (2) ◽  
pp. 267-297 ◽  
Author(s):  
Oleg Davydov
Keyword(s):  

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