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An AdaptiveWavelet Method for Solving High-Dimensional Elliptic PDEs

机译:求解高维椭圆PDE的自适应小波方法

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摘要

Adaptive tensor product wavelet methods are applied for solving Poisson’s equation, as well as anisotropic generalizations, in high space dimensions. It will be demonstrated that the resulting approximations converge in energy norm with the same rate as the best approximations from the span of the best N tensor product wavelets, where moreover the constant factor that we may lose is independent of the space dimension n. The cost of producing these approximations will be proportional to their length with a constant factor that may grow with n, but only linearly.
机译:自适应张量积小波方法被用于求解高空间维度中的泊松方程以及各向异性概括。将会证明,所得的近似值在能量范数中以与最佳N张量积子波的跨度中的最佳近似值相同的速率收敛。此外,我们可能损失的常数因子与空间维数n无关。产生这些近似值的成本将与它们的长度成比例,并且具有一个可能随n增加但恒定的线性常数。

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