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首页> 外文期刊>Journal of applied mathematics >Piecewise bivariate hermite interpolations for large sets of scattered data
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Piecewise bivariate hermite interpolations for large sets of scattered data

机译:大型分散数据集的分段双变量Hermite插值

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摘要

The requirements for interpolation of scattered data are high accuracy and high efficiency. In this paper, a piecewise bivariate Hermite interpolant satisfying these requirements is proposed. We firstly construct a triangulation mesh using the given scattered point set. Based on this mesh, the computational point (x,y) is divided into two types: interior point and exterior point. The value of Hermite interpolation polynomial on a triangle will be used as the approximate value if point (x,y) is an interior point, while the value of a Hermite interpolation function with the form of weighted combination will be used if it is an exterior point. Hermite interpolation needs the first-order derivatives of the interpolated function which is not directly given in scatted data, so this paper also gives the approximate derivative at every scatted point using local radial basis function interpolation. And numerical tests indicate that the proposed piecewise bivariate Hermite interpolations are economic and have good approximation capacity.
机译:对散乱数据进行插值的要求是高精度和高效率。本文提出了满足这些要求的分段二元Hermite插值。我们首先使用给定的散点集构造一个三角剖分网格。基于此网格,计算点(x,y)分为两种类型:内部点和外部点。如果点(x,y)是内部点,则将三角形上的Hermite内插多项式的值用作近似值,而如果外部是点,则将使用加权组合形式的Hermite内插函数的值点。 Hermite插值需要插值函数的一阶导数,但在散点数据中并未直接给出,因此,本文还使用局部径向基函数插值给出了每个散点上的近似导数。数值试验表明,提出的分段二元Hermite插值是经济的,并且具有良好的近似能力。

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