Collaborative-Prediction-Based Recursive Filtering for Nonlinear Systems Subject to Low-Duty-Cycle Scheduling-Reference-Cited by-同舟云学术

Collaborative-Prediction-Based Recursive Filtering for Nonlinear Systems Subject to Low-Duty-Cycle Scheduling

Published:2024 Issue: Volume:72 Page:480-491
ISSN:1053-587X
Container-title:IEEE Transactions on Signal Processing
language:
Short-container-title:IEEE Trans. Signal Process.

Author:

Gao Hongyu¹^ORCID,Yu Lindong¹^ORCID,Hou Nan²^ORCID,Song Jinbo¹^ORCID,Li Yue¹^ORCID

Affiliation:

1. School of Electrical and Information Engineering, the Artificial Intelligence Energy Research Institute and the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing, China

2. Artificial Intelligence Energy Research Institute and Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing, China

Funder

National Natural Science Foundation of China

Hainan Province Science and Technology Special Fund of China

Natural Science Foundation of Heilongjiang Province

Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/78/10347386/10379562.pdf?arnumber=10379562

Reference52 articles.

1. Finite‐horizon bounded synchronisation and state estimation for discrete‐time complex networks: local performance analysis

2. A variance-constrained approach to recursive state estimation for time-varying complex networks with missing measurements

3. Robust Partial-Nodes-Based State Estimation for Complex Networks Under Deception Attacks

4. Approximation-Free Robust Synchronization Control for Dual Linear Motors Driven Systems With Uncertainties and Disturbances

5. Non-fragile l₂-l_∞ state estimation for time-delayed artificial neural networks: an adaptive event-triggered approach