Efficient and Fast Joint Sparse Constrained Canonical Correlation Analysis for Fault Detection-Reference-Cited by-同舟云学术

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Efficient and Fast Joint Sparse Constrained Canonical Correlation Analysis for Fault Detection

Published:2022 Issue: Volume: Page:1-11
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Xiu Xianchao¹^ORCID,Pan Lili²,Yang Ying³^ORCID,Liu Wanquan⁴^ORCID

Affiliation:

1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China

2. Department of Mathematics, Shandong University of Technology, Zibo, China

3. Department of Mechanics and Engineering Science, Peking University, Beijing, China

4. School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/09887978.pdf?arnumber=9887978

Cited by 4 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. Graph embedding dictionary pair learning for robust process monitoring;Measurement;2024-03

2. Robust generalized canonical correlation analysis;Applied Intelligence;2023-05-17

3. Structured Joint Sparse Orthogonal Nonnegative Matrix Factorization for Fault Detection;IEEE Transactions on Instrumentation and Measurement;2023

4. A Survey on Regularized Sparse Optimization Models and Algorithms;Artificial Intelligence and Robotics Research;2023

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