A handwritten Chinese character classifying algorithm is designed based on the character feature matrix with the excellent classifying effect.
应用字符的特征矩阵设计了一个手写体汉字的分类识别算法，取得了较好的效果。
The simulation results show that the training time of Branched Feedforward Neural Network is obviously reduced and the classifying effect is much better as compared with general BP Network.
仿真结果表明，与一般BP网络相比较，分支前馈神经网络显著地减少了训练时间，且分类效果更好。
The result shows it has better effect of classifying.
结果表明具有良好的分类效果。
应用推荐