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。

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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。

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The result shows it has better effect of classifying.

结果表明具有良好的分类效果。

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