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arXiv 1502.03733math.NAcs.NA
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最大光滑性B-样条的近似误差估计与逆不等式

Approximation error estimates and inverse inequalities for B-splines of maximum smoothness

Johannes Kepler University Linz(林茨约翰·开普勒大学);University of Pavia(帕维亚大学)

Stefan Takacs, Thomas Takacs

AI总结:

本文研究最大光滑性B-样条的近似误差估计及逆不等式,揭示其在Sobolev范数下的特性,为等几何离散化求解偏微分方程提供高效迭代方法基础。

摘要:

本文开发了最大光滑性B-样条的近似误差估计及相应的逆不等式,其中被近似函数和近似误差均在标准Sobolev范数和半范数下测量。所呈现的近似误差估计不依赖于样条的多项式次数,仅取决于网格大小。我们发现近似结果位于经典B-样条空间的子空间中,并展示该子空间存在不依赖多项式次数的逆不等式。由于近似误差估计与逆不等式表现出互补行为,本文结果可用于构造快速迭代方法,以求解由等几何离散化偏微分方程产生的问题。

英文摘要:

In this paper, we develop approximation error estimates as well as corresponding inverse inequalities for B-splines of maximum smoothness, where both the function to be approximated and the approximation error are measured in standard Sobolev norms and semi-norms. The presented approximation error estimates do not depend on the polynomial degree of the splines but only on the grid size. We will see that the approximation lives in a subspace of the classical B-spline space. We show that for this subspace, there is an inverse inequality which is also independent of the polynomial degree. As the approximation error estimate and the inverse inequality show complementary behavior, the results shown in this paper can be used to construct fast iterative methods for solving problems arising from isogeometric discretizations of partial differential equations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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