Fixed time synchronization of delayed chaotic neural networks by using active adaptive control

2021 ◽  
Author(s):  
Haipeng Su ◽  
Runzi Luo ◽  
Jiaojiao Fu ◽  
Meichun Huang
Keyword(s):  
Neural Networks ◽  
Adaptive Control ◽  
Time Synchronization ◽  
Fixed Time ◽  
Chaotic Neural Networks ◽  
Delayed Chaotic Neural Networks

scholarly journals Finite-time synchronization for chaotic neural networks with stochastic disturbances

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Xuejun Shi ◽  
Yongshun Zhao ◽  
Xiaodi Li
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Basic Result ◽  
Fixed Time ◽  
System Response ◽  
Stochastic Disturbances ◽  
Chaotic Neural Networks ◽  
Response System ◽  
Error System

AbstractIn this paper, we focus on the problem of synchronization for chaotic neural networks with stochastic disturbances. Firstly, we provide a basic result that the systems including the drive system, response system, and error system have a unique solution on the whole time horizon. Based on this result, we design a new control law such that the response system can be synchronized with the drive chaotic system in finite time. Furthermore, we show that the settling time is independent of the initial data under some proper conditions, which hints that the fixed-time synchronization of chaotic neural networks can be realized by our proposed method. Finally, we give simulations to verify the theoretical analysis for our main results.

Quasi fixed-time synchronization of memristive Cohen-Grossberg neural networks with reaction-diffusion

2020 ◽  
Vol 415 ◽  
pp. 74-83
Author(s):  
Fangmin Ren ◽  
Minghui Jiang ◽  
Hao Xu ◽  
Mengqin Li
Keyword(s):  
Neural Networks ◽  
Time Synchronization ◽  
Reaction Diffusion ◽  
Fixed Time
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