Quantized Event-Triggered Synchronization of Discrete-Time Chaotic Neural Networks With Stochastic Deception Attack
Author:
Affiliation:
1. School of Control and Computer Engineering, North China Electric Power University, Beijing, China
2. Department of Electrical Engineering, Yeungnam University, Gyeongsan, South Korea
Funder
National Natural Science Foundation of China
Korea Government
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software
Link
http://xplorestaging.ieee.org/ielx7/6221021/10153807/10075400.pdf?arnumber=10075400
Reference47 articles.
1. Dynamical and Static Multisynchronization of Coupled Multistable Neural Networks via Impulsive Control
2. Event-Triggering and Quantized Sliding Mode Control of UMV Systems Under DoS Attack
3. Stability Analysis for Delayed Neural Networks With an Improved General Free-Matrix-Based Integral Inequality
4. Resilient cooperative output regulation for nonlinear multi-agent systems under DoS attacks;zhang;IEEE Trans Autom Control,2022
5. Exponential H? synchronization of general discrete-time chaotic neural networks with or without time delays;qi;IEEE Trans Neural Netw,2010
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