Robust Principal Component Analysis based on Purity-Reference-Cited by-同舟云学术

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Robust Principal Component Analysis based on Purity

Published:2022-08-15 Issue: Volume: Page:
ISSN:
Container-title:2022 34th Chinese Control and Decision Conference (CCDC)
language:
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Author:

Pan Jinyan¹,Cai Yingqi²,Xie Youwei¹,Lin Tingting³,Gao Yunlong³,Cao Chao⁴

Affiliation:

1. Jimei University,School of Information Engineering,Xiamen,China,361021

2. Jimei University,School of Science,Xiamen,China,361021

3. Xiamen University,School of Aerospace Engineering,Xiamen,China,361102

4. Ministry of Natural Resources,Third Institute of Oceanography,Xiamen,P. R. China,361005

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10032843/10032844/10033628.pdf?arnumber=10033628

Reference16 articles.

1. Robust Principal Component Analysis Based on Maximum Correntropy Criterion

2. A size-insensitive integrity-based fuzzy c-means method for data clustering

3. Angle Principal Component Analysis

4. Principal component analysis based on non-parametric maximum entropy

5. $\ell _{2,p}$ -Norm Based PCA for Image Recognition

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Comparative Exploration of PCA Variants for Clustering Analysis;2023 Fourth International Conference on Information Systems and Software Technologies (ICI2ST);2023-11-22

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