确定RBF神经网络隐层节点数的最大矩阵元法

Maximal Matrix Element Method for Determining the Number of Hidden Nodes of RBF Neural Networks

针对基于训练样本输入信息进行非监督聚类来确定RBF神经网络隐层节点数的方法存在利用信息不充分的缺陷,该文提出了一种新的确定RBF神经网络隐层节点数的方法。利用训练样本输入输出全部信息建立样本间的相似矩阵,然后采用最大矩阵元法来确定RBF神经网络隐层节点数。实验仿真表明,该方法是有效的。

Aiming at the shortcoming of the method that hasn't good use of the information of training samples cluster-ing to determine the hidden nodes of RBF neural networks.In this paper,the new method is presented to determine the number of hidden nodes of RBF neural networks,it makes use of the whole inputting and outputting information of training samples to establish similar matrix of samples,then to determine the number of hidden nodes of RBF neural networks by maximal matrix element method.The result of experiment shows that it is feasible.