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引用次数: 1

摘要

利用径向基函数(RBF)插值方法创建和重建高程和地表模型,求解偏微分方程和重建噪声图像。本文分析的RBF计算的分层方法是将输入点的域划分为子域,并对子域计算局部插值径向函数。然后将这些局部函数组合成一个对输入点进行插值的全局函数。HRBF方法的不同之处在于它们对全局域的划分和随后局部函数的连接的方法。本文将重点分析HRBF方法的优缺点,特别是使用基于kd-tree结构的平衡二叉树或网格来划分全局域的方法。
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Analysing the Properties of Hierarchical RBFs for Interpolation
Interpolation methods using radial basis functions (RBF) are used for the creation and reconstruction of elevation and surface models, solving partial differential equations and reconstruction of noisy images. Hierarchical methods of RBF computation (HRBF) analysed in this article are based on the division of the domain of input points into subdomains, for which local interpolating radial functions are computed. These local functions are then combined into one global function interpolating the input points. The difference between HRBF methods lies in their approach to the division of the global domain and the subsequent joining of local functions. This article will focus on the analysis of advantages and disadvantages of HRBF methods, specifically methods using a balanced binary tree based on the kd-tree structure, or a grid to divide the global domain.
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