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A state estimation H∞ issue for discrete-time stochastic impulsive genetic regulatory networks in the presence of leakage, multiple delays and Markovian jumping parameters

Journal of the Franklin Institute ◽

10.1016/j.jfranklin.2017.12.036 ◽

2018 ◽

Vol 355 (5) ◽

pp. 2735-2761 ◽

Cited By ~ 9

Author(s):

S. Pandiselvi ◽

R. Raja ◽

Q. Zhu ◽

G. Rajchakit

Keyword(s):

State Estimation ◽

Discrete Time ◽

Regulatory Networks ◽

Genetic Regulatory Networks ◽

Multiple Delays ◽

Markovian Jumping Parameters ◽

Markovian Jumping

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Mode-dependent state estimation for discrete-time genetic regulatory networks with a random delay described by a Markovian chain

2014 International Conference on Mechatronics and Control (ICMC) ◽

10.1109/icmc.2014.7231682 ◽

2014 ◽

Author(s):

Weijun Ma ◽

Shimo Wang ◽

Yantao Wang

Keyword(s):

State Estimation ◽

Discrete Time ◽

Regulatory Networks ◽

Genetic Regulatory Networks ◽

Random Delay ◽

Markovian Chain ◽

Dependent State

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state estimation of discrete-time markov jump neural networks with general transition probabilities and output quantization

The Journal of Difference Equations and Applications ◽

10.1080/10236198.2017.1368501 ◽

2017 ◽

Vol 23 (11) ◽

pp. 1824-1852 ◽

Cited By ~ 5

Author(s):

R. Sasirekha ◽

R. Rakkiyappan ◽

Jinde Cao ◽

Ying Wan ◽

Ahmed Alsaedi

Keyword(s):

Neural Networks ◽

State Estimation ◽

Discrete Time ◽

Transition Probabilities ◽

Markov Jump

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H∞ state estimation for discrete time-delayed stochastic genetic regulatory networks with known sojourn probabilities

2017 23rd International Conference on Automation and Computing (ICAC) ◽

10.23919/iconac.2017.8081976 ◽

2017 ◽

Cited By ~ 2

Author(s):

Xiongbo Wan ◽

Zidong Wang ◽

Chuanyu Ren

Keyword(s):

State Estimation ◽

Discrete Time ◽

Regulatory Networks ◽

Genetic Regulatory Networks ◽

Stochastic Genetic Regulatory Networks

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Distributed Dissipative State Estimation for Markov Jump Genetic Regulatory Networks Subject to Round-Robin Scheduling

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2019.2909747 ◽

2020 ◽

Vol 31 (3) ◽

pp. 762-771 ◽

Cited By ~ 20

Author(s):

Hao Shen ◽

Shicheng Huo ◽

Huaicheng Yan ◽

Ju H. Park ◽

Victor Sreeram

Keyword(s):

State Estimation ◽

Regulatory Networks ◽

Round Robin ◽

Genetic Regulatory Networks ◽

Markov Jump ◽

Dissipative State

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Finite-time H∞ control for discrete-time genetic regulatory networks with random delays and partly unknown transition probabilities

Journal of the Franklin Institute ◽

10.1016/j.jfranklin.2013.05.016 ◽

2013 ◽

Vol 350 (7) ◽

pp. 1944-1961 ◽

Cited By ~ 20

Author(s):

Andong Liu ◽

Li Yu ◽

Dan Zhang ◽

Wen-an Zhang

Keyword(s):

Discrete Time ◽

Finite Time ◽

Regulatory Networks ◽

Transition Probabilities ◽

Genetic Regulatory Networks ◽

Random Delays ◽

Partly Unknown Transition Probabilities

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Robust state estimation for Markov jump genetic regulatory networks based on passivity theory

Complexity ◽

10.1002/cplx.21649 ◽

2015 ◽

Vol 21 (5) ◽

pp. 214-223 ◽

Cited By ~ 4

Author(s):

Li Lu ◽

Bing He ◽

Chuntao Man ◽

Shun Wang

Keyword(s):

State Estimation ◽

Regulatory Networks ◽

Genetic Regulatory Networks ◽

Markov Jump

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Robust state estimation for discrete-time stochastic genetic regulatory networks with probabilistic measurement delays

Neurocomputing ◽

10.1016/j.neucom.2012.12.011 ◽

2013 ◽

Vol 111 ◽

pp. 1-12 ◽

Cited By ~ 27

Author(s):

Tong Wang ◽

Yongsheng Ding ◽

Lei Zhang ◽

Kuangrong Hao

Keyword(s):

State Estimation ◽

Discrete Time ◽

Regulatory Networks ◽

Genetic Regulatory Networks ◽

Stochastic Genetic Regulatory Networks

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Finite-Time H∞ State Estimation for Discrete Time-Delayed Stochastic Switched Genetic Regulatory Networks with Uncertain Sojourn Probabilities

2018 37th Chinese Control Conference (CCC) ◽

10.23919/chicc.2018.8482595 ◽

2018 ◽

Author(s):

REN Chuanyu ◽

WAN Xiongbo

Keyword(s):

State Estimation ◽

Discrete Time ◽

Finite Time ◽

Regulatory Networks ◽

Genetic Regulatory Networks

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Event-triggered H ∞ state estimation for discrete-time stochastic genetic regulatory networks with Markovian jumping parameters and time-varying delays

Neurocomputing ◽

10.1016/j.neucom.2015.10.017 ◽

2016 ◽

Vol 174 ◽

pp. 912-920 ◽

Cited By ~ 136

Author(s):

Qi Li ◽

Bo Shen ◽

Yurong Liu ◽

Fuad E. Alsaadi

Keyword(s):

State Estimation ◽

Discrete Time ◽

Regulatory Networks ◽

Genetic Regulatory Networks ◽

Time Varying ◽

Markovian Jumping Parameters ◽

Markovian Jumping ◽

Stochastic Genetic Regulatory Networks ◽

Event Triggered

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Robust non-fragile H∞ state estimation for discrete-time genetic regulatory networks with Markov jump delays and uncertain transition probabilities

A state estimation H∞ issue for discrete-time stochastic impulsive genetic regulatory networks in the presence of leakage, multiple delays and Markovian jumping parameters

Mode-dependent state estimation for discrete-time genetic regulatory networks with a random delay described by a Markovian chain

state estimation of discrete-time markov jump neural networks with general transition probabilities and output quantization

H∞ state estimation for discrete time-delayed stochastic genetic regulatory networks with known sojourn probabilities

Distributed Dissipative State Estimation for Markov Jump Genetic Regulatory Networks Subject to Round-Robin Scheduling

Finite-time H∞ control for discrete-time genetic regulatory networks with random delays and partly unknown transition probabilities

Robust state estimation for Markov jump genetic regulatory networks based on passivity theory

Robust state estimation for discrete-time stochastic genetic regulatory networks with probabilistic measurement delays

Finite-Time H∞ State Estimation for Discrete Time-Delayed Stochastic Switched Genetic Regulatory Networks with Uncertain Sojourn Probabilities

Event-triggered H ∞ state estimation for discrete-time stochastic genetic regulatory networks with Markovian jumping parameters and time-varying delays

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