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arXiv 0808.0487math.NAcs.NA
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多元快速离散Walsh变换及其在函数插值中的应用

A Multivariate Fast Discrete Walsh Transform with an Application to Function Interpolation

Hong Kong Baptist University(香港浸会大学);University of New South Wales(新南威尔士大学);Illinois Institute of Technology(伊利诺伊理工学院)

Kwong-Ip Liu, Josef Dick, Fred J. Hickernell

AI总结:

本文提出一种针对数字网采样数据的多元快速离散Walsh变换算法,计算复杂度为O(N log N),并用于函数插值及有效维数估计。

摘要:

对于高维问题(如逼近和积分),由于维数灾难,无法在网格上采样。一个有吸引力的替代方案是在低差异集(如积分格或数字网)上采样。本文介绍了一种针对数字网采样数据的多元快速离散Walsh变换,仅需$O(N \log N)$次运算,其中$N$是数据点数。该算法及其逆变换是多元快速傅里叶变换的数字模拟。该快速离散Walsh变换及其逆变换可用于逼近函数的Walsh系数,然后构造函数的样条插值。该插值可用于估计函数的有效维数,这是数值多元积分理论中的一个重要概念。给出了各种函数的数值结果。

英文摘要:

For high dimensional problems, such as approximation and integration, one cannot afford to sample on a grid because of the curse of dimensionality. An attractive alternative is to sample on a low discrepancy set, such as an integration lattice or a digital net. This article introduces a multivariate fast discrete Walsh transform for data sampled on a digital net that requires only $O(N \log N)$ operations, where $N$ is the number of data points. This algorithm and its inverse are digital analogs of multivariate fast Fourier transforms. This fast discrete Walsh transform and its inverse may be used to approximate the Walsh coefficients of a function and then construct a spline interpolant of the function. This interpolant may then be used to estimate the function's effective dimension, an important concept in the theory of numerical multivariate integration. Numerical results for various functions are presented.

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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