Data-driven fault identifiability analysis for discrete-time dynamic systems-Reference-Cited by-同舟云学术

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Data-driven fault identifiability analysis for discrete-time dynamic systems

Published:2020-01-25 Issue:2 Volume:51 Page:404-412
ISSN:0020-7721
Container-title:International Journal of Systems Science
language:en
Short-container-title:International Journal of Systems Science

Author:

Fu Fangzhou¹²,Wang Dayi³,Li Wenbo²,Li Fanbiao⁴

Affiliation:

1. School of Aeronautics and Astronautic, Sun Yat-sen University, Guangzhou, People's Republic of China

2. Beijing Institute of Control Engineering, China Academy of Space Technology, Beijing, People's Republic of China

3. Beijing Institute of Spacecraft System Engineering, China Academy of Space Technology, Beijing, People's Republic of China

4. School of Information Science and Engineering, Central South University, Changsha, People's Republic of China

Publisher

Informa UK Limited

Subject

Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207721.2020.1716101

Reference40 articles.

1. Empirical Non-Parametric Estimation of the Fisher Information

2. Alarm correlation and fault identification in communication networks

3. Mutual Information, Fisher Information, and Population Coding

4. Detectability of microwave background polarization

5. ReliableH∞control for nonlinear discrete-time systems with multiple intermittent faults in sensors or actuators

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3. Data-driven fault diagnosis analysis and open-set classification of time-series data;Control Engineering Practice;2022-04

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