Checked by the experiments, the improved RBF network has less hidden neural units than before, at the same time keep the accurate of RBF based classifier.
经实验证明，基于改进后的RBF网络具有更少的隐含神经元，但仍然保持了基于RBF网络分类器的准确率。
The choice of the center of radial basis function, constructing an improved RBF network and its application to recognize the trained samples and test samples were discussed.
讨论了径向基函数中心的选取，构造了改进的RBF网络对训练样本和测试样本进行识别。
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。
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