Robust Principal Component Analysis Based on Maximum Correntropy Criterion
文献类型：期刊论文
| 作者 | He, Ran1 ; Hu, Bao-Gang1; Zheng, Wei-Shi2; Kong, Xiang-Wei3; Ran He(赫然); Baogang Hu
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| 刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
 |
| 出版日期 | 2011-06-01 |
| 卷号 | 20期号:6页码:1485-1494 |
| 关键词 | Correntropy half-quadratic optimization principal component analysis (PCA) robust |
| 英文摘要 | Principal component analysis (PCA) minimizes the mean square error (MSE) and is sensitive to outliers. In this paper, we present a new rotational-invariant PCA based on maximum correntropy criterion (MCC). A half-quadratic optimization algorithm is adopted to compute the correntropy objective. At each iteration, the complex optimization problem is reduced to a quadratic problem that can be efficiently solved by a standard optimization method. The proposed method exhibits the following benefits: 1) it is robust to outliers through the mechanism of MCC which can be more theoretically solid than a heuristic rule based on MSE; 2) it requires no assumption about the zero-mean of data for processing and can estimate data mean during optimization; and 3) its optimal solution consists of principal eigenvectors of a robust covariance matrix corresponding to the largest eigen-values. In addition, kernel techniques are further introduced in the proposed method to deal with nonlinearly distributed data. Numerical results demonstrate that the proposed method can outperform robust rotational-invariant PCAs based on norm when outliers occur. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | FACE RECOGNITION ; SIGNAL ; IMAGE |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000290732600002 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/2813]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 自动化研究所_智能感知与计算研究中心 离退休人员 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510275, Guangdong, Peoples R China 3.Dalian Univ Technol, Sch Elect & Informat Engn, Dalian 116024, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Ran,Hu, Bao-Gang,Zheng, Wei-Shi,et al. Robust Principal Component Analysis Based on Maximum Correntropy Criterion[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2011,20(6):1485-1494. |
| APA | He, Ran,Hu, Bao-Gang,Zheng, Wei-Shi,Kong, Xiang-Wei,Ran He,&Baogang Hu.(2011).Robust Principal Component Analysis Based on Maximum Correntropy Criterion.IEEE TRANSACTIONS ON IMAGE PROCESSING,20(6),1485-1494. |
| MLA | He, Ran,et al."Robust Principal Component Analysis Based on Maximum Correntropy Criterion".IEEE TRANSACTIONS ON IMAGE PROCESSING 20.6(2011):1485-1494. |
入库方式： OAI收割
来源：自动化研究所
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