designing hidden layer nodes 隐层结点设计
If the number of the BP neural network’hidden layer nodes is decided according to needing,a neural network hasing three layers can approximate a continuous function with any precision.
如果BP神经网络的隐层节点数可以根据需要自由决定，那么一个三层神经网络可以实现以任意精度近似任意连续函数。
参考来源 - 小波神经网络及其应用·2,447,543篇论文数据，部分数据来源于NoteExpress
First, the usual ways that are employed to choose the number of RBFNN's hidden layer nodes are analyzed and compared.
首先对目前常用的RBF网络的隐层节点数的选择办法进行了分析，并指出它们的优点和不足。
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 RBF network configuration is formulated as a minimization problem with respect to the number of hidden layer nodes, the center locations and the connection weights.
R BF网络的设计问题就是关于网络隐节点数和隐层节点RBF函数中心、宽度和隐层到输出层的权值的性能指标的最小化问题。
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