Optimized general sparse grid approximation spaces for operator equations

Optimized general sparse grid approximation spaces for operator equations
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算子方程的优化一般稀疏网格近似空间

DOI:
10.1090/s0025-5718-09-02248-0
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发表时间:
2009
期刊:
Math. Comput.
影响因子:
--
通讯作者:
S. Knapek
S. Knapek
中科院分区:
--
文献类型:
--
作者:
M. Griebel;S. Knapek

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本文关注任意阶椭圆伪微分算子的优化稀疏网格逼近空间的构造。基于张量积双正交小波基和稳定子空间分裂的框架,在满足解的某些附加正则性假设的情况下,构造了尺寸小于标准全网格空间但具有与标准全网格空间相同的逼近阶的算子自适应子空间。特别是对于正序算子,与整个网格空间相比,它们的维度与问题的维度无关。此外,对于负序运算符,总体成本显着有利于新的近似空间。我们给出连续线性信息情况下的成本估计。我们通过提出伽辽金方法和最佳预处理,以建设性的方式展示了这些结果。该理论涵盖椭圆边值问题以及边界积分方程。参考
This paper is concerned with the construction of optimized sparse grid approximation spaces for elliptic pseudodifferential operators of arbitrary order. Based on the framework of tensor-product biorthogonal wavelet bases and stable subspace splittings, we construct operator-adapted subspaces with a dimension smaller than that of the standard full grid spaces but which have the same approximation order as the standard full grid spaces, provided that certain additional regularity assumptions on the solution are fulfilled. Specifically for operators of positive order, their dimension isindependent of the dimensionof the problem, compared tofor the full grid space. Also, for operators of negative order the overall cost is significantly in favor of the new approximation spaces. We give cost estimates for the case of continuous linear information. We show these results in a constructive manner by proposing a Galerkin method together with optimal preconditioning. The theory covers elliptic boundary value problems as well as boundary integral equations. References
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