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RBF++_1.2
- 径向基RBF多维空间插值算法，用于空间散乱点曲面重建，优于多项式插值-RBF RBF multidimensional spatial interpolation algorithm for space scattered surface reconstruction, better than polynomial interpolation
radial-basis-function-network
- 用于函数逼近的径向基逼近和差值，是一个基础函数，包括高斯及二项式两种，可拓展到多个应用领域-Radial basis functions are use for function approximation and interpolation. This package supports two popular classes of rbf: Gaussian and Polyharmonic Splines (of which the Thin Plate Spline is a subcla
RBF_Interp
- RBF方法对一维函数进行插值实例，选用的函数为MQ函数，可与高阶多项式插值对比，说明RBF方法克服了龙格振荡问题。-RBF method for one dimentional function interpolation, where the Runge oscillation is disappear.
RBF
- 径向基函数网络(RBF)特点：1)可用于任意维空间的插值；2)训练速度和插值速度较慢；3)一旦训练成功，只要存储权系数矩阵即可，适用于海量数据的插值；4)当数据不全时，可以用于数据补全。 -Radial basis function (RBF) network features: 1) can be used in any dimensional space interpolation 2) interpolation and the training speed slower 3) o
rbfyubp-biye
- 运用c++语言，实现了BP网络和RBF网络的数据以及空间插值功能-C++ use language to achieve a data BP network and RBF network and the spatial interpolation function
RBF
- Radial Basis Function interpolation-RBF was originally developed for scattered multivariate data interpolation (Hardy 1971). It uses a series of basis functions that are symmetric and centred at each sampling point. Radial basis functions are a s
rbfinterp
- 利用径向基函数进行函数插值，例子中包括一维和二维的情况，尤其是二维，生成插值的时候尽量不用双循环(Using radial basis function interpolation, examples include one-dimensional and two-dimensional, especially two-dimensional, when interpolation, as far as possible without double loop)
RBF
- 径向基函数插值使用一系列基函数，它们在每个采样点对称且居中。径向基函数是一类特殊的函数，其主要特征是它们的响应与中心点的距离单调地减小（或增加）。中心、距离刻度和精确的形状是模型的参数。(Radial Basis Function interpolation with biharmonic, multiquadric, inverse multiquadric, thin plate spline, and Gaussian basis functions for Matlab/Octave.
dace
- 几种常用代理模型算法，包括Kriging,RBF,样条插值模型。能够根据样本数据拟合高精度代理模型，并提供了几个算例(Several commonly used proxy model algorithms, including Kriging,RBF, spline interpolation model.According to the sample data, the high precision proxy model can be fitted, and several example