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基于比例移动最小二乘近似的误差分析

王青青 李小林

王青青, 李小林. 基于比例移动最小二乘近似的误差分析[J]. 应用数学和力学, 2017, 38(11): 1289-1299. doi: 10.21656/1000-0887.370260
引用本文: 王青青, 李小林. 基于比例移动最小二乘近似的误差分析[J]. 应用数学和力学, 2017, 38(11): 1289-1299. doi: 10.21656/1000-0887.370260
WANG Qing-qing, LI Xiao-lin. Error Analysis of the Scaled Moving Least Squares Approximation[J]. Applied Mathematics and Mechanics, 2017, 38(11): 1289-1299. doi: 10.21656/1000-0887.370260
Citation: WANG Qing-qing, LI Xiao-lin. Error Analysis of the Scaled Moving Least Squares Approximation[J]. Applied Mathematics and Mechanics, 2017, 38(11): 1289-1299. doi: 10.21656/1000-0887.370260

基于比例移动最小二乘近似的误差分析

doi: 10.21656/1000-0887.370260
基金项目: 国家自然科学基金(面上项目)(11471063);重庆市基础科学与前沿技术研究重点项目 (cstc2015jcyjBX0083);重庆市教委科学技术研究项目(KJ1600330)
详细信息
    作者简介:

    王青青(1992—),女,硕士(通讯作者. E-mail: 379680348@qq.com);李小林(1983—),男,教授,博士,博士生导师.

  • 中图分类号: O242.2

Error Analysis of the Scaled Moving Least Squares Approximation

Funds: The National Natural Science Foundation of China(General Program)(11471063)
  • 摘要: 相较于移动最小二乘近似方法,比例移动最小二乘近似法有效地克服了前者带来的矩阵病态这一问题,展示出了更好的数值稳定性和更高的计算精度.给出了比例移动最小二乘近似对函数及其任意阶导数的误差估计,并给出了数值算例来验证之前的理论分析结果,通过与移动最小二乘近似的比较,表明比例移动最小二乘近似能得到更快的收敛性和更稳定的计算性.
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出版历程
  • 收稿日期:  2016-08-26
  • 修回日期:  2017-09-28
  • 刊出日期:  2017-11-15

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