| FUZZY PRINCIPAL COMPONENT ANALYSIS AND ITS KERNEL- BASED MODEL |
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| 作者姓名： | Wu Xiaohong Zhou Jianjiang |
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| 作者单位： | [1]College of Information Science ＆ Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China [2]College of Electrical ＆ Information Engineering, Jiangsu University, Zhenjiang 212013, China |
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| 摘 要： | Principal Component Analysis(PCA)is one of the most important feature extraction methods,and Kernel Principal Component Analysis(KPCA)is a nonlinear extension of PCA based on kernel methods.In real world,each input data may not be fully assigned to one class and it may partially belong to other classes.Based on the theory of fuzzy sets,this paper presents Fuzzy Principal Component Analysis(FPCA)and its nonlinear extension model,i.e.,Kernel-based Fuzzy Principal Component Analysis(KFPCA).The experimental results indicate that the proposed algorithms have good performances.
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| 关 键 词： | 计算机技术 网络设计 设计方案 通信技术 信息处理 |
| 修稿时间： | 2006-03-13 |
Fuzzy principal component analysis and its Kernel-based model |
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| Wu Xiaohong Zhou Jianjiang.FUZZY PRINCIPAL COMPONENT ANALYSIS AND ITS KERNEL- BASED MODEL[J].Journal of Electronics,2007,24(6):772-775. |
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| Authors: | Wu Xiaohong Zhou Jianjiang |
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| Affiliation: | 1. College of Information Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Electrical & Information Engineering, Jiangsu University, Zhenjiang 212013, China
2. College of Information Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China |
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| Abstract: | Principal Component Analysis(PCA)is one of the most important feature extraction methods,and Kernel Principal Component Analysis(KPCA)is a nonlinear extension of PCA based on kernel methods.In real world,each input data may not be fully assigned to one class and it may partially belong to other classes.Based on the theory of fuzzy sets,this paper presents Fuzzy Principal Component Analysis(FPCA)and its nonlinear extension model,i.e.,Kernel-based Fuzzy Principal Component Analysis(KFPCA).The experimental results indicate that the proposed algorithms have good performances. |
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| Keywords: | Principal Component Analysis(PCA) Kernel methods Fuzzy PCA(FPCA) Kernel PCA(KPCA) |
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