The classification mechanism of a radial basis function network (RBFN) is investigated in this paper.
本文研究了径向基函数网络(RBFN)的分类机理问题。
A two-level learning method combining improved immune algorithm and least square method was proposed to design a radial basis function (RBF) network.
结合改进的免疫算法和最小二乘法，提出了一种设计径向基函数(RBF)网络的两级学习方法。
The experimental data are used to train a radial basis function (RBF) artificial neural network, and the construction and parameters of the network are obtained for data fusion.
实验数据被用来训练径向基函数(RBF)神经网络，得出的神经网络结构和参数用于数据融合。
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