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 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。
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。
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