Adaptive event-triggered H∞ filtering for discrete-time delayed neural networks with randomly occurring missing measurements

Signal Processing ◽

10.1016/j.sigpro.2018.07.027 ◽

2018 ◽

Vol 153 ◽

pp. 221-230 ◽

Author(s):

Huijiao Wang ◽

Anke Xue

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Missing Measurements ◽

Delayed Neural Networks ◽

Event Triggered

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Finite-Time H∞ Estimator Design for Switched Discrete-Time Delayed Neural Networks With Event-Triggered Strategy

IEEE Transactions on Cybernetics ◽

10.1109/tcyb.2020.2992518 ◽

2020 ◽

pp. 1-13

Author(s):

Hong Sang ◽

Jun Zhao

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Finite Time ◽

Delayed Neural Networks ◽

Estimator Design ◽

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 ◽

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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Finite-time resilient H∞ state estimation for discrete-time delayed neural networks under dynamic event-triggered mechanism

Neural Networks ◽

10.1016/j.neunet.2019.09.006 ◽

2020 ◽

Vol 121 ◽

pp. 356-365 ◽

Author(s):

Yufei Liu ◽

Bo Shen ◽

Huisheng Shu

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Finite Time ◽

Delayed Neural Networks ◽

Dynamic Event ◽

Event Triggered

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Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizations

Systems Science & Control Engineering ◽

10.1080/21642583.2018.1531360 ◽

2018 ◽

Vol 6 (3) ◽

pp. 74-84 ◽

Author(s):

Tingting Zhang ◽

Jinfeng Gao ◽

Jiahao Li

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Markov Jump ◽

Delayed Neural Networks ◽

Event Triggered

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L2 − L∞ state estimation for discrete-time delayed neural networks with missing measurements and randomly occurring sensor linearity

2016 35th Chinese Control Conference (CCC) ◽

10.1109/chicc.2016.7554503 ◽

2016 ◽

Author(s):

Hao Zhang ◽

Huaicheng Yan ◽

Hongbo Shi ◽

Hao Zhang

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Missing Measurements ◽

Delayed Neural Networks

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H ∞ State Estimation of Discrete Time Delayed Neural Networks with Multiple Missing Measurements Using Second Order Reciprocal Convex Approach

Advances in Intelligent Systems and Computing - Computational Intelligence, Cyber Security and Computational Models ◽

10.1007/978-981-10-0251-9_12 ◽

2015 ◽

pp. 109-119 ◽

Author(s):

K. Maheswari

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Second Order ◽

Missing Measurements ◽

Delayed Neural Networks

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Finite-time event-triggered non-fragile state estimation for discrete-time delayed neural networks with randomly occurring sensor nonlinearity and energy constraints

Neurocomputing ◽

10.1016/j.neucom.2019.12.038 ◽

2020 ◽

Vol 384 ◽

pp. 115-129 ◽

Author(s):

Yamin Wang ◽

Arunkumar Arumugam ◽

Yurong Liu ◽

Fuad E. Alsaadi

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Finite Time ◽

Fragile State ◽

Delayed Neural Networks ◽

Energy Constraints ◽

Event Triggered

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Distributed reliable L2 — L∞ state estimation for discrete-time delayed neural networks with missing measurements

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

10.1109/wcica.2016.7578562 ◽

2016 ◽

Author(s):

Hao Zhang ◽

Huaicheng Yan ◽

Mengling Wang ◽

Hongbo Shi

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Missing Measurements ◽

Delayed Neural Networks

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H∞ state estimation for discrete-time delayed neural networks with randomly occurring quantizations and missing measurements

Neurocomputing ◽

10.1016/j.neucom.2014.06.017 ◽

2015 ◽

Vol 148 ◽

pp. 388-396 ◽

Author(s):

Jie Zhang ◽

Zidong Wang ◽

Derui Ding ◽

Xiaohui Liu

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Missing Measurements ◽

Delayed Neural Networks

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