An Improved ART1 Neural Network Algorithm for Character Recognition
The paper indicates the shortage of standard ART1 neural network, and an improved calculating method of similarity is presented. The corresponding place value of two vectors at the same time is considered in this method. The method avoids the different result of ART1 neural network because of inputting different sequence. In order to solve the pattern excursion problem of ART1 neural network, the principle of minority subordinate to majority is proposed to reduce the appeared problem. They improve the applicative effect of ART1 neural network.
ART1 neural network Pattern recognition Character process
Peng Li Ma Xianxi
School of Communication and Control Engineering, Jiangnan University, Wu Xi, China, 214122
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
2946-2949
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）