摘要
文中提出了应用学习子空间法的通信信号自动分类的网络结构,通过将输入矢量在子空间内的投影实现聚类运算,达到了将隐含层节点数降低的目的,提高了网络的训练速度,增强了网络的抗干扰和实时处理能力.文中还对加噪后的通信信号进行计算机模拟实现了分类.
This paper presents a structure of the neural network for automatic classification of radio-communication signals using the learning subspace method.Nodes of the hidden layer are re-duced by parity operation of input vectors in subspace.The structure increases the trainning speed,the capability of countering interference and the ability for real time operation.Radio communication signals with noise are classified by computer simulation.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
1995年第1期89-93,共5页
Journal of Xidian University