Universal Approximation Using Radial-Basis-Function Networks
Universal Approximation Using Radial-Basis-Function Networks
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DOI：
10.1162/neco.1991.3.2.246
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发表时间：
1991-06-01
影响因子：
2.9
通讯作者：
Sandberg, I. W.
中科院分区：
文献类型：
--
作者：
Park, J.;Sandberg, I. W.
关于前馈网络的最新研究以及近似有限数量的实际变量功能的问题的问题。其中一些研究涉及隐藏层非线性不是乙状结肠的案例。这是由使用非烟叶隐藏层单元成功应用的馈电网络的动机。本文报告有关径向基础功能（RBF）网络（RBF）网络的报告，并且证明具有一个隐藏层的RBF网络能够具有通用近似值的RBF网络。在这里，重点是典型的RBF网络的情况，结果表明，在每个核节点中具有相同平滑因子的某些类别的RBF网络足够宽，足以进行通用近似。
There have been several recent studies concerning feedforward networks and the problem of approximating arbitrary functionals of a finite number of real variables. Some of these studies deal with cases in which the hidden-layer nonlinearity is not a sigmoid. This was motivated by successful applications of feedforward networks with nonsigmoidal hidden-layer units.This paper reports on a related study of radial-basis-function (RBF) networks, and it is proved that RBF networks having one hidden layer are capable of universal approximation. Here the emphasis is on the case of typical RBF networks, and the results show that a certain class of RBF networks with the same smoothing factor in each kernel node is broad enough for universal approximation.