摘要
首先提出黑白特征分离(即黑白特征局部和整体分离提取特征的思想)和一种BP神经网络的快速收敛算法及训练策略,并在此基础上构造了5种独立的识别模块.应用加权表决方法设计了识别带有手写干扰的印刷体数字及一些特殊字符的综合方法,取得了理想的效果.
A blackwhite feature separate concept(that is extractting blackwhite feature locally and totally) and a BP neural network fast algrithm and trian strategy are proposed. Five independent matching models are further constructed. Then a roubst method, which is used to recognize figures and special symbols interfered by handwritting, is developped and satisfactory results are obtained.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
1998年第1期21-24,共4页
Journal of Xi'an Jiaotong University