| 完全判别分析 |
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| 引用本文： | 霍红文,封举富.完全判别分析[J].中国科学：信息科学,2012(9):1181-1190. |
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| 作者姓名： | 霍红文 封举富 |
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| 作者单位： | 中国电子技术标准化研究院;北京大学信息科学技术学院,机器感知与智能教育部重点实验室 |
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| 基金项目： | 国家重点基础研究发展计划(批准号:2011CB302400)资助项目 |
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| 摘 要： | 针对现有的线性判别分析算法中存在的降维舍弃空间的判别信息丢失问题,以及秩空间和零空间的判别信息难以兼顾的问题,本文提出了一种完全判别分析算法.算法通过新构建一个子空间以及其中的判别矩阵,实现了可以充分使用全空间的判别信息;且新空间的维数较低,算法流程简单,计算代价较小.相关实验结果证实了本文算法较传统判别分析算法有更好的性能和效率.
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| 关 键 词： | 判别分析 子空间 秩空间 零空间 人脸识别 |
Complete discriminant analysis |
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| HUO HongWen,& FENG JuFu.Complete discriminant analysis[J].Scientia Sinica Informationis,2012(9):1181-1190. |
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| Authors: | HUO HongWen & FENG JuFu |
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| Affiliation: | 1 China Electronics Standardization Institute,Beijing 100007,China;2 School of Electronics Engineering and Computer Science,Peking University,Key Laboratory of Machine Perception,MOE,Beijing 100871,China |
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| Abstract: | This paper proposes a complete discriminant analysis algorithm to solve the problem that existing linear discriminative analysis algorithms always miss discriminant information when reducing dimensions,and the problem that it is difficult to juggle discriminant information both in rank space and null space.This algorithm makes full use of all discriminant information in all space,by constructing a new subspace and its discriminant matrix.The dimension of the new subspace is low and the algorithm is simple and costless.The experimental results demonstrate that this algorithm has better performance and efficiency than traditional discriminant analysis algorithms. |
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| Keywords: | discriminant analysis subspace rank space null space face recognition |
| 本文献已被 CNKI 等数据库收录！ |
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