Avoiding Optimal Mean Calculation Robust PCA Based on the Nested ℓ<sub>P</sub> -Norm and ℓ<sub>2,p</sub> -Norm-Reference-Cited by-同舟云学术

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Avoiding Optimal Mean Calculation Robust PCA Based on the Nested ℓ_P -Norm and ℓ_2,p -Norm

Published:2023-10-27 Issue: Volume:32 Page:497-502
ISSN:
Container-title:2023 9th Annual International Conference on Network and Information Systems for Computers (ICNISC)
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Author:

Gao Yunlong¹,Xu Zhenghong¹,Cao Chao²

Affiliation:

1. Xiamen University,Pen-Tung Sah Institute of Micro-Nano Science and Technology,Xiamen,China

2. Ministry of Natural Resources,Third Institute of Oceanography, Ministry of Natural Resources Key Laboratory of Marine Ecological Conservation and Restoration,Xiamen,China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10473310/10473311/10473380.pdf?arnumber=10473380

Reference12 articles.

1. Robust L₁ Norm Factorization in the Presence of Outliers and Missing Data by Alternative Convex Programming

2. R1-PCA

3. Principal Component Analysis by $L_{p}$ -Norm Maximization

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

5. Nuclear Norm-Based 2-DPCA for Extracting Features From Images

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