| 模式特征滤波 |
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| 引用本文： | 郑永凯,张凌,董守斌.模式特征滤波[J].计算机工程,2001,27(10):32-33,143. |
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| 作者姓名： | 郑永凯 张凌 董守斌 |
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| 作者单位： | 华南理工大学网络中心 |
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| 基金项目： | 广东省自然科学基金项目，高等学校骨干(980603)，老师资助计划项目()[2000]65 |
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| 摘 要： | 借鉴了传统的信号频谱滤波原理，根据最小均方误差原则，在特征空间法模式识别中提出了“特征空间维纳滤波”算法，它充分利用先验知识，为模式识别系统构造一个线性滤波器；理论和实验结果表明，维纳滤波使总偏差达到最小，实验结果还表明它对识别性能有一定改善。
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| 关 键 词： | 模式识别 人脸识别 特征空间 特征滤波器 |
| 文章编号： | 1000-3428(2001)10-0032-02 |
Pattern Feature Filtering |
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| ZHENG Yongkai,ZHANG Ling,DONG Shoubin.Pattern Feature Filtering[J].Computer Engineering,2001,27(10):32-33,143. |
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| Authors: | ZHENG Yongkai ZHANG Ling DONG Shoubin |
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| Abstract: | Traditional signal frequency filtering theory is used for reference in this paper. According to the least mean square (LMS) deviation rule, an algorithm named 'eigenspace Wiener filtering' that constructs a linear filter for the recognition system taking full advantage of prior knowledge is presented in pattern recognition using eigenspace method. The algorithm as well as experiment shows that it results in the least deviation; and the experiment tells that it improves the recognition performance in a certain extent. |
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| Keywords: | Pattern recognition Face recognition Eigenspace Feature filter |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
