Event-triggered recursive state estimation for dynamical networks under randomly switching topologies and multiple missing measurements

Automatica ◽

10.1016/j.automatica.2020.108908 ◽

2020 ◽

Vol 115 ◽

pp. 108908 ◽

Cited By ~ 8

Author(s):

Jun Hu ◽

Zidong Wang ◽

Guo-Ping Liu ◽

Chaoqing Jia ◽

Jonathan Williams

Keyword(s):

State Estimation ◽

Missing Measurements ◽

Dynamical Networks ◽

Switching Topologies ◽

Recursive State Estimation ◽

Event Triggered

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Event-Triggered Recursive State Estimation for Stochastic Complex Dynamical Networks Under Hybrid Attacks

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2021.3105409 ◽

2021 ◽

pp. 1-13

Author(s):

Yun Chen ◽

Xueyang Meng ◽

Zidong Wang ◽

Hongli Dong

Keyword(s):

State Estimation ◽

Complex Dynamical Networks ◽

Dynamical Networks ◽

Recursive State Estimation ◽

Event Triggered

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Recursive state estimation for discrete-time nonlinear systems with event-triggered data transmission, norm-bounded uncertainties and multiple missing measurements

International Journal of Robust and Nonlinear Control ◽

10.1002/rnc.3527 ◽

2016 ◽

Vol 26 (17) ◽

pp. 3673-3695 ◽

Cited By ~ 28

Author(s):

Xiujuan Zheng ◽

Huajing Fang

Keyword(s):

Nonlinear Systems ◽

State Estimation ◽

Discrete Time ◽

Data Transmission ◽

Missing Measurements ◽

Recursive State Estimation ◽

Bounded Uncertainties ◽

Norm Bounded Uncertainties ◽

Event Triggered

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Event-Triggered $H_\infty$ State Estimation for Delayed Stochastic Memristive Neural Networks With Missing Measurements: The Discrete Time Case

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2017.2728639 ◽

2018 ◽

Vol 29 (8) ◽

pp. 3726-3737 ◽

Cited By ~ 49

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Memristive Neural Networks ◽

Missing Measurements ◽

Discrete Time Case ◽

Event Triggered

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Event-Triggered H∞ State Estimation for Delayed Stochastic Memristive Neural Networks with Missing Measurements: The Discrete Time Case

Stability Analysis and State Estimation of Memristive Neural Networks ◽

10.1201/9781003189152-3 ◽

2021 ◽

pp. 33-54

Author(s):

Hongjian Liu ◽

Zidong Wang ◽

Lifeng Ma

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Memristive Neural Networks ◽

Missing Measurements ◽

Discrete Time Case ◽

Event Triggered

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An event-triggered recursive state estimation approach for time-varying nonlinear complex networks with quantization effects

Neurocomputing ◽

10.1016/j.neucom.2020.09.074 ◽

2021 ◽

Vol 426 ◽

pp. 104-113

Author(s):

F. Rahimi ◽

H. Rezaei

Keyword(s):

Complex Networks ◽

State Estimation ◽

Time Varying ◽

Recursive State Estimation ◽

Event Triggered

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Event-Triggered Particle Filter for State Estimation of Non-linear Stochastics Hybrid System with Missing Measurements

2020 International Conference on Inventive Computation Technologies (ICICT) ◽

10.1109/icict48043.2020.9112379 ◽

2020 ◽

Author(s):

Robinson P. Paul ◽

Vishvjit K. Thakar ◽

Hetal Patel

Keyword(s):

Particle Filter ◽

State Estimation ◽

Hybrid System ◽

Missing Measurements ◽

Non Linear ◽

Event Triggered

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A Scalable Algorithm for Event-Triggered State Estimation With Unknown Parameters and Switching Topologies Over Sensor Networks

IEEE Transactions on Cybernetics ◽

10.1109/tcyb.2019.2917543 ◽

2020 ◽

Vol 50 (9) ◽

pp. 4087-4097 ◽

Cited By ~ 8

Author(s):

Derui Ding ◽

Zidong Wang ◽

Qing-Long Han

Keyword(s):

Sensor Networks ◽

State Estimation ◽

Unknown Parameters ◽

Scalable Algorithm ◽

Switching Topologies ◽

Event Triggered

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Event-triggered synchronization strategy for complex dynamical networks with the Markovian switching topologies

Neural Networks ◽

10.1016/j.neunet.2015.11.002 ◽

2016 ◽

Vol 74 ◽

pp. 52-57 ◽

Cited By ~ 87

Author(s):

Aijuan Wang ◽

Tao Dong ◽

Xiaofeng Liao

Keyword(s):

Markovian Switching ◽

Complex Dynamical Networks ◽

Dynamical Networks ◽

Switching Topologies ◽

Event Triggered

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Optimized state estimation for nonlinear dynamical networks subject to fading measurements and stochastic coupling strength: An event-triggered communication mechanism

Kybernetika ◽

10.14736/kyb-2020-1-0035 ◽

2020 ◽

pp. 35-56

Author(s):

Chaoqing Jia ◽

Jun Hu ◽

Chongyang Lv ◽

Yujing Shi

Keyword(s):

State Estimation ◽

Coupling Strength ◽

Dynamical Networks ◽

Nonlinear Dynamical ◽

Communication Mechanism ◽

Event Triggered

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Recursive state estimation for time-varying complex networks subject to missing measurements and stochastic inner coupling under random access protocol

Neurocomputing ◽

10.1016/j.neucom.2018.07.086 ◽

2019 ◽

Vol 346 ◽

pp. 48-57 ◽

Cited By ~ 47

Author(s):

Hongxu Zhang ◽

Jun Hu ◽

Hongjian Liu ◽

Xiaoyang Yu ◽

Fengqiu Liu

Keyword(s):

Complex Networks ◽

State Estimation ◽

Random Access ◽

Time Varying ◽

Missing Measurements ◽

Access Protocol ◽

Random Access Protocol ◽

Recursive State Estimation

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