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arXiv 1503.00907math.NAcs.NA
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用于$C^1$五次样条的空间的高斯求积规则

Gaussian quadrature rules for $C^1$ quintic splines

King Abdullah University of Science and Technology(阿卜杜拉国王科技大学)

Michael Bartoň, Rachid Ait-Haddou, Victor Manuel Calo

AI总结:

本文提出用于$C^1$五次样条空间的高斯求积规则,通过显式递推公式确定节点和权重,无需数值求解器,且规则最优,每个子区间仅需两个节点,计算成本降低2/3,数值实验显示随着$n$增大,快速收敛到Hughes等人对于无限域的两三分规则。

摘要:

我们为具有均匀结点序列的有限域上的$C^1$五次样条空间提供了显式表达的求积规则。求积节点和权重通过显式递推公式确定,避免了任何数值求解器的干预,该规则最优,即需要最少的节点数。对于每个$n$个子区间,通常仅需两个节点,与多项式经典高斯求积相比,计算成本降低了2/3。数值实验显示,随着$n$的增长,快速收敛到Hughes等人对于无限域的两三分规则。

英文摘要:

We provide explicit expressions for quadrature rules on the space of $C^1$ quintic splines with uniform knot sequences over finite domains. The quadrature nodes and weights are derived via an explicit recursion that avoids an intervention of any numerical solver and the rule is optimal, that is, it requires the minimal number of nodes. For each of $n$ subintervals, generically, only two nodes are required which reduces the evaluation cost by $2/3$ when compared to the classical Gaussian quadrature for polynomials. Numerical experiments show fast convergence, as $n$ grows, to the "two-third" quadrature rule of Hughes et al. for infinite domains.

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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