Description: Radial basis functions are used 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 subclass).
The package also calculates line integrals between two points.
For more information, see blog.nutaksas.com for academic papers.
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Description: 径向基函数神经网络Matlab源代码,非常实用-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 subclass).
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Description: 自己编写RBF神经网络程序，RBF神经网络隐层采用标准Gaussian径向基函数，输出层采用线性激活函数，其中数据中心、扩展常数和输出权值均用梯度法求解，它们的学习率均为0.001。其中隐节点数选为10，初始输出权值取[-0.1，0.1]内的随机值，初始数据中心取[-1，1]内的随机值，初始扩展常数取[0.1，0.3]内的随机值，输入采用[0 1]的随机阶跃输入(Write your own RBF neural network, RBF neural network hidden layer using standard Gaussian radial basis function, the output layer using a linear activation function, the data center, and the output weights are constant expansion with the gradient method, the learning rate is 0.001. The number of hidden nodes is 10, the initial output value [-0.1, random value of 0.1], initial data center [-1, random value of 1], the initial expansion constant of [0.1, a random value within 0.3], using a random order [0 1] step input) Platform: |
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Description: 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.
RBF interpolation uses a series of basis functions that are symmetric and centered at each sampling point. Radial basis functions are a special class of functions with their main feature being that their response decreases (or increases) monotonically with distance from a central point. The center, the distance scale, and the precise shape are parameters of the model.) Platform: |
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Search - matlab RBF Gaussian