Interpretable fault detection using projections of mutual information matrix
From MaRDI portal
Publication:2027446
DOI10.1016/j.jfranklin.2021.02.016zbMath1464.93009arXiv2007.10692OpenAlexW3131773838MaRDI QIDQ2027446
Shujian Yu, Chenglin Wen, Jose C. Principe, Feiya Lv
Publication date: 26 May 2021
Published in: Journal of the Franklin Institute (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2007.10692
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- A Mathematical Theory of Communication
- Model-based fault diagnosis techniques. Design schemes, algorithms and tools
- Diagnosis of poor control-loop performance using higher-order statistics
- Reconstruction-based contribution for process monitoring
- Recursive transformed component statistical analysis for incipient fault detection
- Multivariate Statistical Process Control with Industrial Applications
- Measures of Entropy From Data Using Infinitely Divisible Kernels
- Mutual Information Matrices Are Not Always Positive Semidefinite
- Statistical Theory of the Energy Levels of Complex Systems. I
- Information Theoretic Learning
- On quantum Rényi entropies: A new generalization and some properties
- Infinitely Divisible Matrices
- RELATIONS BETWEEN TWO SETS OF VARIATES
- Fault detection and diagnosis in industrial systems
This page was built for publication: Interpretable fault detection using projections of mutual information matrix