Zeroing Neural Network for Solving Time-Varying Linear Equation and Inequality Systems

2019 ◽  
Vol 30 (8) ◽  
pp. 2346-2357 ◽  
Author(s):  
Feng Xu ◽  
Zexin Li ◽  
Zhuoyun Nie ◽  
Hui Shao ◽  
Dongsheng Guo
Keyword(s):  
Neural Network ◽  
Linear Equation ◽  
Time Varying ◽  
Inequality Systems

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>

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>

Real-domain QR decomposition models employing zeroing neural network and time-discretization formulas for time-varying matrices

2021 ◽  
Vol 448 ◽  
pp. 217-227
Author(s):  
Zhenyu Li ◽  
Yunong Zhang ◽  
Liangjie Ming ◽  
Jinjin Guo ◽  
Vasilios N. Katsikis
Keyword(s):  
Neural Network ◽  
Time Discretization ◽  
Qr Decomposition ◽  
Time Varying ◽  
Real Domain ◽  
Decomposition Models
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