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Scattered data interpolation by bivariate splines with higher approximation order

机译:通过具有更高逼近阶的二元样条进行散乱数据插值

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摘要

Given a set of scattered data, we usually use a minimal energy method to find a Lagrange interpolation in a bivariate spline space over a triangulation of the scattered data locations. It is known that the approximation order of the minimal energy spline interpolation is only 2 in terms of the size of triangulation. To improve this order of approximation, we propose several new schemes in this paper. Mainly we follow the ideas of clamped cubic interpolatory splines and not-a-knot interpolatory splines in the univariate setting and extend them to the bivariate setting. In addition, instead of the energy functional of the second order, we propose to use higher order versions. We shall present some theoretical analysis as well as many numerical results to demonstrate that our new interpolation schemes indeed have a higher order of approximation than the classic minimal energy interpolatory spline.
机译:给定一组分散的数据,我们通常使用最小能量方法在分散数据位置的三角剖分的二元样条空间中找到Lagrange插值。众所周知,就三角剖分的大小而言,最小能量样条插值的近似阶数仅为2。为了提高这种近似阶数,我们在本文中提出了几种新方案。我们主要遵循单变量设置中的三次三次插值样条和非节点插值样条的思想,并将其扩展到双变量设置。另外,我们建议使用高阶版本代替二阶能量函数。我们将提供一些理论分析以及许多数值结果,以证明我们的新插值方案确实比经典的最小能量插值样条曲线具有更高的逼近度。

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