Robust Low-Rank Latent Feature Analysis for Spatiotemporal Signal Recovery-Reference-Cited by-同舟云学术

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Robust Low-Rank Latent Feature Analysis for Spatiotemporal Signal Recovery

Published:2023 Issue: Volume: Page:1-14
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Wu Di¹^ORCID,Li Zechao²^ORCID,Yu Zhikai³,He Yi⁴^ORCID,Luo Xin¹^ORCID

Affiliation:

1. College of Computer and Information Science, Southwest University, Chongqing, China

2. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China

3. School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China

4. Department of Computer Science, Old Dominion University, Norfolk, VA, USA

Funder

National Natural Science Foundation of China

Science and Technology Foundation of State Grid Corporation of China

Chongqing Technical Innovation and Application Development Special Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10361831.pdf?arnumber=10361831

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