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径向基函数网络(Radial Basis Function,RBF)是由三层构成的前向网络:第一层为输入层,节点数等于输入的维数;第二层为隐含层,节点个数视问题复杂度而定;第三层为输出层,节点数等于输出数据的维度。RBF的隐含层是非线性的,采用径向基函数作为基函数,从而将输入向量空间转换到隐含层空间,使原来的线性不可分问题变为线性可分,输出层则是线性的。
径向基神经网络可以分为正则化网络和广义网络,在实践中被广泛应用的是广义网络。
A radial basis function (RBF) is a real-valued function whose value depends only on the distance from the origin, so that; or alternatively on the distance from some other point , called a center, so that .
Any function that satisfies the property is a radial function. The norm is usually Euclidean distance, although other distance functions are also possible.
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原文地址:https://www.cnblogs.com/larry-xia/p/9251044.html