中文摘要：

通过标准自适应共振理论神经网络（Adaptive Resonance Theory,ART）,设计和实现了一个字符识别器,针对标准的ART1网络存在的不足,即网络的学习不稳定,对样本输入顺序比较敏感等问题,给出了改进方法,用C语言实现了这2种字符识别器,实验结果表明这2种字符识别器能够对不同的字符进行识别,改进方法比基于标准ART1网络具有更好的稳定性.

英文摘要：

Adaptive Resonance Theory（ART） neural network is analyzed in this paper. A character recognizer is designed and implemented based on the standard ART1 network, aiming at the shortcomings of the standard ART1 network, which concludes the unstablity of network learning and the over sensitiveness to the input sample sequence.This paper gives a method to improve the implementation in C 2 kind of identifier. Experimental validation of these two character recognizer can identify the different character. The improvement method based on standard ART1 network has better stability.