Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements

By Jun Hu, Zidong Wang, Huijun Gao, Lampros K. Stergioulas. at - Automatisierungstechnik, 2012

349 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/859cdeed4fa5f28adf54b12dead52ace2d8e0e69

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Zidong Wang
2. Huijun Gao
3. Jun Hu
4. Qing-Long Han

In Computer Networks and Communications

1. Zidong Wang
2. Huijun Gao
3. Hongli Dong
4. Jun Hu
5. Xiaohui Liu
6. Hamid Reza Karimi
7. Qing-Long Han
8. James Lam

In Control and Systems Engineering

1. Zidong Wang
2. Huijun Gao
3. Hongli Dong
4. Jun Hu
5. Qing-Long Han
6. James Lam
7. Tongwen Chen
8. Peng Shi

Citations in the corpus

• A variance-constrained approach to recursive state estimation for time-varying complex networks with missing measurements (2016, neutral): “In reality, the system states are not always available due probably to physical constraints, technological restrictions or expensive cost for measuring [5, 7, 12].”
• Recent Advances on Recursive Filtering and Sliding Mode Design for Networked Nonlinear Stochastic Systems: A Survey (2013, background): “(i) In [153, 154], the recursive filtering problems have been investigated for two classes of time-varying nonlinear stochastic systems.”