Finite-Time Stabilization of Neutral Hopfield Neural Networks with Mixed Delays

2018 ◽  
Vol 48 (3) ◽  
pp. 1645-1669 ◽  
Author(s):  
Chaouki Aouiti ◽  
Foued Miaadi
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Hopfield Neural Networks ◽  
Mixed Delays ◽  
Finite Time Stabilization

Finite-Time Synchronization of Complex-Valued Neural Networks with Mixed Delays and Uncertain Perturbations

2017 ◽  
Vol 46 (1) ◽  
pp. 271-291 ◽  
Author(s):  
Chao Zhou ◽  
Wanli Zhang ◽  
Xinsong Yang ◽  
Chen Xu ◽  
Jianwen Feng
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Mixed Delays ◽  
Complex Valued

scholarly journals Finite-Time Stabilization for Stochastic Inertial Neural Networks with Time-Delay via Nonlinear Delay Controller

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Deyi Li ◽  
Yuanyuan Wang ◽  
Guici Chen ◽  
Shasha Zhu
Keyword(s):  
Neural Networks ◽  
Time Delay ◽  
Finite Time ◽  
Design Method ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Nonlinear Feedback ◽  
Inertial Neural Networks ◽  
Finite Time Stabilization

This paper pays close attention to the problem of finite-time stabilization related to stochastic inertial neural networks with or without time-delay. By establishing proper Lyapunov-Krasovskii functional and making use of matrix inequalities, some sufficient conditions on finite-time stabilization are obtained and the stochastic settling-time function is also estimated. Furthermore, in order to achieve the finite-time stabilization, both delayed and nondelayed nonlinear feedback controllers are designed, respectively, in terms of solutions to a set of linear matrix inequalities (LMIs). Finally, a numerical example is provided to demonstrate the correction of the theoretical results and the effectiveness of the proposed control design method.

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