Chang Liu

Orcid: 0000-0003-2195-6178

Affiliations:

Guangdong University of Technology, School of Automation, Guangdong Key Laboratory of IoT Information Technology, Guangzhou, China

According to our database¹, Chang Liu authored at least 21 papers between 2018 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Bibliography

2024

Event-Triggered Distributed Moving Horizon Estimation Over Wireless Sensor Networks.

[BibT_eX]

[DOI]

IEEE Trans. Ind. Informatics, March, 2024

2023

State Estimation for Nonuniformly Sampled Neural Networks With Hidden Information.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Syst., October, 2023

Synchronization for Markovian master-slave neural networks: an event-triggered impulsive approach.

[BibT_eX]

[DOI]

Int. J. Syst. Sci., September, 2023

Consensus-based distributed moving horizon estimation with constraints.

[BibT_eX]

[DOI]

Inf. Sci., August, 2023

Bounded synchronization for uncertain master-slave neural networks: An adaptive impulsive control approach.

[BibT_eX]

[DOI]

Neural Networks, May, 2023

Finite-Time Estimation for Markovian BAM Neural Networks With Asymmetrical Mode-Dependent Delays and Inconstant Measurements.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2023

Reliable mixed H2/H∞ distributed estimation for periodic nonlinear systems with jumping topology.

[BibT_eX]

[DOI]

J. Frankl. Inst., 2023

Set-Membership Filtering for Time-Varying Complex Networks with Randomly Varying Nonlinear Coupling Structure.

[BibT_eX]

[DOI]

Circuits Syst. Signal Process., 2023

2022

Set-membership filtering for complex networks with constraint communication channels.

[BibT_eX]

[DOI]

Neural Networks, 2022

Finite-time synchronisation for periodic delayed master-slave neural networks with weighted try-once-discard protocol.

[BibT_eX]

[DOI]

Int. J. Syst. Sci., 2022

Reliable state estimation for neural networks with TOD protocol and mixed compensation.

[BibT_eX]

[DOI]

Neurocomputing, 2022

2021

Reliable impulsive synchronization for fuzzy neural networks with mixed controllers.

[BibT_eX]

[DOI]

Neural Networks, 2021

Finite-time synchronization for periodic T-S fuzzy master-slave neural networks with distributed delays.

[BibT_eX]

[DOI]

J. Frankl. Inst., 2021

2020

Finite-Horizon H<sub>∞</sub> State Estimation for Time-Varying Neural Networks with Periodic Inner Coupling and Measurements Scheduling.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Syst., 2020

Nonfragile Finite-Time Synchronization for Coupled Neural Networks With Impulsive Approach.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2020

Anti-synchronization for periodic BAM neural networks with Markov scheduling protocol.

[BibT_eX]

[DOI]

Neurocomputing, 2020

2019

Finite-Horizon $l_2-l_\infty$ Synchronization for Time-Varying Markovian Jump Neural Networks Under Mixed-Type Attacks: Observer-Based Case.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2019

Trajectory Tracking With Constrained Sensors and Unreliable Communication Networks.

[BibT_eX]

[DOI]

IEEE Access, 2019

2018

Remote Estimator Design for Time-Delay Neural Networks Using Communication State Information.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2018

Finite-time control for periodic systems with Markov jump sensor nonlinearities and random input gains.

[BibT_eX]

[DOI]

J. Frankl. Inst., 2018

State estimation for neural networks with jumping interval weight matrices and transmission delays.

[BibT_eX]

[DOI]

Neurocomputing, 2018

Chang Liu

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