摘要： 汉字识别是汉语、汉字认知研究的一个重要研究领域。该文提出了一个基于多层自组织神经网络的模型，从汉字字形聚类及汉字部件拆分的角度，对基于汉字认知的汉字识别过程进行了初步的探索。模拟研究结果表明，模型通过学习能够识别出汉字的结构类型和部件，发现汉字识别中的规律，在一定程度上模拟了汉字的识别。

关键词: 汉字认知, 汉字识别, 自组织特征映射, 聚类, 计算机模拟

Abstract: Chinese characters recognition is an important research field in Chinese characters cognition. This paper proposes a model based on multi-layer self-organizing neural network. The process of Chinese characters recognition based on Chinese characters cognition is researched from the aspect of Chinese characters cluster and components splitting. Results from this simulation suggest that the model is able to recognize the architecture and components of Chinese characters. It can detect some rules of Chinese characters recognition by learning. So it can simulate the process of Chinese characters recognition to some exteht.

Key words: Chinese characters cognition, Chinese characters recognition, Self-organizing map, Cluster, Computer simulation

中图分类号: 

• TP18