Jun Wang

Affiliations:
  • Southwest Minzu University, College of Electrical and Information Engineering, Key Laboratory of Electronic Information of State Ethnic Affairs Commission, Chengdu, China


According to our database1, Jun Wang authored at least 11 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Enhanced cubic function negative-determination Lemma on stability analysis for delayed neural networks via new analytical techniques.
J. Frankl. Inst., 2024

2023
Intelligence Sampling Control Algorithm for T-S Fuzzy Networked Control Systems via Cloud Server Storage Method Under DoS Attack.
Int. J. Fuzzy Syst., September, 2023

2022
New results for T-S fuzzy systems with hybrid communication delays.
Fuzzy Sets Syst., 2022

2021
Fuzzy quantized sampled-data control for extended dissipative analysis of T-S fuzzy system and its application to WPGSs.
J. Frankl. Inst., 2021

2020
Hybrid-driven finite-time <i>H</i><sub>∞</sub> sampling synchronization control for coupling memory complex networks with stochastic cyber attacks.
Neurocomputing, 2020

Non-fragile memory filtering of T-S fuzzy delayed neural networks based on switched fuzzy sampled-data control.
Fuzzy Sets Syst., 2020

Reliable asynchronous sampled-data filtering of T-S fuzzy uncertain delayed neural networks with stochastic switched topologies.
Fuzzy Sets Syst., 2020

Robust <i>H</i><sub>∞</sub> control for uncertain delayed T-S fuzzy systems with stochastic packet dropouts.
Appl. Math. Comput., 2020

2019
New reliable nonuniform sampling control for uncertain chaotic neural networks under Markov switching topologies.
Appl. Math. Comput., 2019

2018
Stochastic switched sampled-data control for synchronization of delayed chaotic neural networks with packet dropout.
Appl. Math. Comput., 2018

2017
Sampled-data synchronization control for Markovian delayed complex dynamical networks via a novel convex optimization method.
Neurocomputing, 2017


  Loading...