State estimation for asynchronous sensor systems with Markov jumps and multiplicative noises

Information Sciences ◽

10.1016/j.ins.2017.07.001 ◽

2017 ◽

Vol 417 ◽

pp. 1-19 ◽

Author(s):

Hang Geng ◽

Zidong Wang ◽

Yan Liang ◽

Yuhua Cheng ◽

Fuad E. Alsaadi

Keyword(s):

State Estimation ◽

Sensor Systems ◽

Multiplicative Noises

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State estimation for discrete-time Markov jump linear systems with multiplicative noises and delayed mode measurements

Digital Signal Processing ◽

10.1016/j.dsp.2014.04.002 ◽

2014 ◽

Vol 30 ◽

pp. 27-36 ◽

Author(s):

Wei Liu ◽

Guangzhen Hu

Keyword(s):

State Estimation ◽

Linear Systems ◽

Discrete Time ◽

Markov Jump ◽

Jump Linear Systems ◽

Multiplicative Noises ◽

Markov Jump Linear Systems

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Distributed fusion filter for multi-rate multi-sensor systems with multiplicative noises

2015 34th Chinese Control Conference (CCC) ◽

10.1109/chicc.2015.7260362 ◽

2015 ◽

Author(s):

Jin Hao ◽

Ma Jing

Keyword(s):

Sensor Systems ◽

Multiplicative Noises ◽

Distributed Fusion

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Distributed ℓ2 — ℓ∞ state estimation for periodic systems with multiplicative noises

2016 12th World Congress on Intelligent Control and Automation (WCICA) ◽

10.1109/wcica.2016.7578486 ◽

2016 ◽

Author(s):

Renquan Lu ◽

Jun-Yi Li ◽

Yong Xu ◽

Hui Peng

Keyword(s):

State Estimation ◽

Periodic Systems ◽

Multiplicative Noises

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State estimation for stochastic discrete-time systems with multiplicative noises and unknown inputs over fading channels

Applied Mathematics and Computation ◽

10.1016/j.amc.2017.09.008 ◽

2018 ◽

Vol 320 ◽

pp. 116-130 ◽

Author(s):

Yueyang Li ◽

Shuai Liu ◽

Maiying Zhong ◽

Steven X. Ding

Keyword(s):

State Estimation ◽

Fading Channels ◽

Discrete Time ◽

Unknown Inputs ◽

Multiplicative Noises ◽

Discrete Time Systems ◽

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Optimal Linear State Estimation for Discrete-time Systems with Time-correlated Multiplicative Noises and Delays

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9189629 ◽

2020 ◽

Author(s):

LiLi Kong ◽

Wei Wang

Keyword(s):

State Estimation ◽

Discrete Time ◽

Multiplicative Noises ◽

Discrete Time Systems ◽

Optimal Linear ◽

Linear State ◽

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State estimation for stochastic time‐varying multisensor systems with multiplicative noises: Centralized and decentralized data fusion

Asian Journal of Control ◽

10.1002/asjc.2103 ◽

2019 ◽

Vol 21 (4) ◽

pp. 1547-1555 ◽

Author(s):

Mehdi Rahmani ◽

Mahdi Abolhasani

Keyword(s):

Data Fusion ◽

State Estimation ◽

Time Varying ◽

Multisensor Systems ◽

Multiplicative Noises ◽

Decentralized Data Fusion ◽

Stochastic Time

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Decentralized robust set-valued state estimation in networked multiple sensor systems

Computers & Mathematics with Applications ◽

10.1016/j.camwa.2010.01.032 ◽

2010 ◽

Vol 59 (8) ◽

pp. 2636-2646 ◽

Author(s):

Teddy M. Cheng ◽

Veerachai Malyavej ◽

Andrey V. Savkin

Keyword(s):

State Estimation ◽

Sensor Systems ◽

Multiple Sensor

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Dynamic event-based state estimation for delayed artificial neural networks with multiplicative noises: A gain-scheduled approach

Neural Networks ◽

10.1016/j.neunet.2020.08.023 ◽

2020 ◽

Vol 132 ◽

pp. 211-219 ◽

Author(s):

Shuai Liu ◽

Zidong Wang ◽

Yun Chen ◽

Guoliang Wei

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

State Estimation ◽

Multiplicative Noises ◽

Dynamic Event ◽

Artificial Neural ◽

Event Based ◽

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A decentralized fixed-interval deconvolution algorithm for multi-sensor systems with multiplicative noises

Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788) ◽

10.1109/wcica.2004.1340914 ◽

2004 ◽

Author(s):

Dongsheng Chu ◽

Lu Wang ◽

Zheng Shi

Keyword(s):

Fixed Interval ◽

Sensor Systems ◽

Multiplicative Noises ◽

Deconvolution Algorithm

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Information fusion algorithms for state estimation in multi-sensor systems with correlated missing measurements

Applied Mathematics and Computation ◽

10.1016/j.amc.2013.10.068 ◽

2014 ◽

Vol 226 ◽

pp. 548-563 ◽

Author(s):

R. Caballero-Águila ◽

I. García-Garrido ◽

J. Linares-Pérez

Keyword(s):

State Estimation ◽

Information Fusion ◽

Sensor Systems ◽

Missing Measurements

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