本文应用HMM概率模型和神经网络结合，对联机手写数字和数学符号进行识别。
We recognize on-line handwritten figure and some mathematic characters using the HMM neural networks, and achieve a better result.
提出一个基于多重曲率计算的角点检测算法，对联机手写汉字识别中的笔划拐点进行提取。
An algorithm for stroke corner detection based on curvature multi-calculation is proposed to extract characteristics for OLCCR (on-line handwritten Chinese character recognition).
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