Fixed-time synchronization of time-varying delayed stochastic neural network and its application to secure communication

2019 ◽  
Author(s):  
Chengrong Xie ◽  
Yuning Wu ◽  
Shunqiang Yun ◽  
Guoqiao You ◽  
Yuhua Xu
Keyword(s):  
Neural Network ◽  
Secure Communication ◽  
Time Synchronization ◽  
Fixed Time ◽  
Time Varying ◽  
Stochastic Neural Network

Fixed-time synchronization of memristor-based fuzzy cellular neural network with time-varying delay

2018 ◽  
Vol 355 (14) ◽  
pp. 6780-6809 ◽  
Author(s):  
Mingwen Zheng ◽  
Lixiang Li ◽  
Haipeng Peng ◽  
Jinghua Xiao ◽  
Yixian Yang ◽  
...  
Keyword(s):  
Neural Network ◽  
Time Synchronization ◽  
Fixed Time ◽  
Cellular Neural Network ◽  
Time Varying ◽  
Time Varying Delay ◽  
Fuzzy Cellular Neural Network ◽  
Varying Delay

scholarly journals Globally fixed-time synchronization of coupled neutral-type neural network with mixed time-varying delays

PLoS ONE ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. e0191473 ◽  
Author(s):  
Mingwen Zheng ◽  
Lixiang Li ◽  
Haipeng Peng ◽  
Jinghua Xiao ◽  
Yixian Yang ◽  
...  
Keyword(s):  
Neural Network ◽  
Time Synchronization ◽  
Neutral Type ◽  
Fixed Time ◽  
Time Varying

scholarly journals A varying-gain ZNN model with fixed-time convergence and noise-tolerant performance for time-varying linear equation and inequality systems

2021 ◽  
Author(s):  
Miaomiao Zhang
Keyword(s):  
Neural Network ◽  
Linear Equation ◽  
Design Parameter ◽  
Nonlinear Function ◽  
Fixed Time ◽  
Time Varying ◽  
Bounded Noise ◽  
Inequality Systems ◽  
Zhang Neural Network ◽  
Noise Tolerant

<div>In this paper, a varying-gain zeroing (or Zhang) neural network (VG-ZNN) is proposed to obtain the online solution of the time-varying linear equation and inequality system. Distinguished from the fixed-value design parameter in</div><div>the original zeroing (or Zhang) neural network (ZNN) models, the design parameter of the VG-ZNN model is a nonlinear function that changes with time. The VG-ZNN model composed of the new time-varying design parameter we proposed can achieve fixed-time convergence and tolerate time-varying bounded noise and time-varying derivable noise. The theoretical detailed analysis of the convergence and robustness of the VG-ZNN model are given.</div>

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