Comparison of Radial Basis Functions

被引：2
|
作者：
Rozhenko, A., I [1 ]
机构：
[1] Russian Acad Sci, Inst Computat Math & Math Geophys, Siberian Branch, Pr Akad Laurenteva 6, Novosibirsk 630090, Russia
来源：
NUMERICAL ANALYSIS AND APPLICATIONS | 2018年 / 11卷 / 03期
基金：
俄罗斯基础研究基金会;
关键词：
spline; algorithm; radial basis function; reproducing kernel; trend; external drift; interpolation; smoothing; regression; tension spline; regularized spline;
D O I：
10.1134/S1995423918030047
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A survey of algorithms for approximation of multivariate functions with radial basis function (RBF) splines is presented. Algorithms of interpolating, smoothing, selecting the smoothing parameter, and regression with splines are described in detail. These algorithms are based on the feature of conditional positive definiteness of the spline radial basis function. Several families of radial basis functions generated by means of conditionally completely monotone functions are considered. Recommendations for the selection of the spline basis and preparation of initial data for approximation with the help of the RBF spline are given.
引用
收藏
页码：220 / 235
页数：16
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