Multi-degree B-splines

Algorithmic computation and properties

Journal Article (2020)
Author(s)

D. Toshniwal (The University of Texas at Austin, TU Delft - Numerical Analysis)

Hendrik Speleers (University of Rome Tor Vergata)

René R. Hiemstra (The University of Texas at Austin)

Carla Manni (University of Rome Tor Vergata)

Thomas J.R. Hughes (The University of Texas at Austin)

Research Group
Numerical Analysis
DOI related publication
https://doi.org/10.1016/j.cagd.2019.101792
More Info
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Publication Year
2020
Language
English
Research Group
Numerical Analysis
Volume number
76
Pages (from-to)
1-16

Abstract

This paper addresses theoretical considerations behind the algorithmic computation of polynomial multi-degree spline basis functions as presented in Toshniwal et al. (2017). The approach in Toshniwal et al. (2017) breaks from the reliance on computation of integrals recursively for building B-spline-like basis functions that span a given multi-degree spline space. The gains in efficiency are indisputable; however, the theoretical robustness needs to be examined. In this paper, we show that the construction of Toshniwal et al. (2017) yields linearly independent functions with the minimal support property that span the entire multi-degree spline space and form a convex partition of unity.

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