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arXiv 1210.1682math.NAcs.NA
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径向基函数逼近的一种新的稳定基

A new stable basis for RBF approximation

Gabriele Santin

AI总结:

针对径向基函数逼近中简单平移基导致病态条件的问题,基于核矩阵分解提出一种加权奇异值分解导出的正交基,并给出插值与离散最小二乘逼近的收敛估计和稳定性界。

摘要:

众所周知,如果使用简单的平移基,径向基函数逼近会遭受病态条件的影响。M.Pazouki 和 R.Schaback 最近的工作给出了一种相当通用的方法,基于核矩阵 A 的分解,为原生空间构建稳定的正交基。从该设置出发,我们描述了一种特定的正交基,它源于 A 的加权奇异值分解。该基与导致所谓特征基的紧算子的离散化相关,并提供了与之的联系。我们给出了基于该基的插值和离散最小二乘逼近的收敛估计和稳定性界,其中涉及该算子的特征值。

英文摘要:

It's well know that Radial Basis Function approximants suffers of bad conditioning if the simple basis of translates is used. A recent work of M.Pazouki and R.Schaback gives a quite general way to build stable, orthonormal bases for the native space based on a factorization of the kernel matrix A. Starting from that setting we describe a particular orthonormal basis that arises from a weighted singular value decomposition of A. This basis is related to a discretization of the compact operator which leads to the so-called eigenbasis, and provides a connection with it. We give convergence estimates and stability bound for the interpolation and the discrete least-squares approximation based on this basis, which involves the eigenvalues of such an operator.

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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