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首页> 外文期刊>Journal of Scientific Computing >RBF-Based Partition of Unity Methods for Elliptic PDEs: Adaptivity and Stability Issues Via Variably Scaled Kernels
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RBF-Based Partition of Unity Methods for Elliptic PDEs: Adaptivity and Stability Issues Via Variably Scaled Kernels

机译:椭圆PDE的基于RBF的统一方法划分:通过可变尺度的核的适应性和稳定性问题

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摘要

We investigate adaptivity issues for the approximation of Poisson equations via radial basis function-based partition of unity collocation. The adaptive residual subsampling approach is performed with quasi-uniform node sequences leading to a flexible tool which however might suffer from numerical instability due to ill-conditioning of the collocation matrices. We thus develop a hybrid method which makes use of the so-called variably scaled kernels. The proposed algorithm numerically ensures the convergence of the adaptive procedure.
机译:我们研究基于径向基函数的单位搭配分区对泊松方程逼近的适应性问题。自适应残差二次采样方法是使用准均匀节点序列执行的,从而导致了一种灵活的工具,但是由于配置矩阵的条件不佳,该工具可能会出现数值不稳定的情况。因此,我们开发了一种混合方法,该方法利用了所谓的可变比例内核。所提出的算法在数值上确保了自适应过程的收敛性。

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