A new nonparametric regression learning algorithm for RBF neural network is presented. It is a novel method involving a combination between regression trees and RBF networks.
介绍了一种新的非参数回归RBF神经网络学习算法，该算法将R BF神经网络与回归树结合起来使用。
Compared with RBF Network, it is concluded that learning algorithm is master key to improve properties of Artificial Neural Network.
与工具箱的RBF网络相比较，说明网络的学习算法是改善网络性能的关键。
Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
This paper presents a learning algorithm for a RBF neural network with adjustable radial basis width and discusses its application in the classification problem of share tendency patterns.
提出一个基宽度可调的RBF神经网络学习算法，并将它应用于个股走势模式的分类问题。
As for it, by improving learning algorithm of traditional RBF neural network, a new dynamic cluster-based self-generated method for hidden layer nodes is proposed.
对此，本文改进了R BF神经网络的学习算法，提出了一种基于聚类的动态自生成隐含层节点的思想。
The learning algorithm of membership function based on the RBF Neural Network is discussed and an example is given to demonstrate the validity of this algorithm.
文中探讨了一种用于提取模糊规则的RBF神经网络结构，提出了基于此网路结构的模糊隶属度函数学习算法，最后给出了用于验证该算法有效性的仿真实例。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is studied.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
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