| 基于粗糙集正域的手写字母识别算法 |
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| 引用本文： | 唐朝辉,陈玉明,吴克寿. 基于粗糙集正域的手写字母识别算法[J]. 计算机工程与应用, 2014, 50(23): 118-121 |
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| 作者姓名： | 唐朝辉 陈玉明 吴克寿 |
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| 作者单位： | 厦门理工学院 计算机科学与技术系，福建 厦门 361024 |
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| 基金项目： | 国家自然科学基金(No.61103246，No.60903203)；厦门理工学院人才科研启动项目(No.YKJ10036R)；厦门理工学院教改项目(No.JGY201315)；福建省教育厅B类项目(No.JB12252S，No.JB14082)；福建省大学生创新创业训练计划项目(No.201411062043)。 |
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| 摘 要： | 针对手写字母识别的特点，结合粗糙集相关理论，提出了一种新的手写字母识别算法。通过对采集的样本进行正态分布假设验证，保证样本的可靠性；利用粗糙集上近似、下近似以及正域概念，对手写样本决策系统进行特征选择以简化决策系统，并进一步提炼手写分类规则。实验结果表明，新算法具有较高的识别准确率，是有效可行的。
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| 关 键 词： | 粗糙集 正域 手写识别 特性选择 监督学习 |
Handwritten letter recognition algorithm based on rough set positive region |
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| TANG Chaohui , CHEN Yuming , WU Keshou. Handwritten letter recognition algorithm based on rough set positive region[J]. Computer Engineering and Applications, 2014, 50(23): 118-121 |
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| Authors: | TANG Chaohui CHEN Yuming WU Keshou |
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| Affiliation: | Department of Computer Science and Technology, Xiamen University of Technology, Xiamen, Fujian 361024, China |
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| Abstract: | According to the characteristics of handwritten letter recognition, a new handwritten letter recognition algorithm is proposed based on the rough set theory. The hypothesis of normal distribution has been tested to ensure the reliability of the collected samples. By using upper approximation, lower approximation, as well as positive region of rough set, feature selection is made in order to simplify the decision-making system. Classification rules are then extracted from the simplified decision-making system. Experimental results show that the new algorithm has higher recognition accuracy, and is feasible and effective. |
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| Keywords: | rough set positive region handwriting recognition feature selection supervised learning |
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