摘要
泛化是前馈神经网络最重要的问题之一。本文从提高泛化能力方面对神经网络的拓扑结构问题进行了分析和研究,给出了基于提高泛化能力的网络拓扑结构构造算法。
Generalization is one of the most important problems of neural networks. This paper analyzes and studies relations between number of hidden layers and units with generalization ability. At last an algorithm for constructing and training neural networks, which aim is to improving generalization ability, is proposed.
出处
《长春光学精密机械学院学报》
1997年第2期63-67,共5页
Journal of Changchun Institute of Optics and Fine Mechanics