Switching probabilistic slow feature extraction for semisupervised industrial inferential modeling-Reference-Cited by-同舟云学术

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Switching probabilistic slow feature extraction for semisupervised industrial inferential modeling

Published:2024-09 Issue: Volume:141 Page:103277
ISSN:0959-1524
Container-title:Journal of Process Control
language:en
Short-container-title:Journal of Process Control

Author:

Jiang Chao^ORCID,Peng Xin^ORCID,Huang Biao,Zhong Weimin

Publisher

Elsevier BV

Reference30 articles.

1. A review on soft sensors for monitoring, control, and optimization of industrial processes;Jiang;IEEE Sens. J.,2020

2. Machine learning for industrial sensing and control: A survey and practical perspective;Lawrence;Control Eng. Pract.,2024

3. Latent variable models in the era of industrial big data: Extension and beyond;Kong;Annu. Rev. Control,2022

4. Slow feature analysis: Unsupervised learning of invariances;Wiskott;Neural Comput.,2002

5. Slow down to go better: A survey on slow feature analysis;Song;IEEE Trans. Neural Netw. Learn. Syst.,2022

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