Finite-time boundedness and stabilization of uncertain switched neural networks with time-varying delay

2015 ◽  
Vol 69 ◽  
pp. 135-143 ◽  
Author(s):  
Yuanyuan Wu ◽  
Jinde Cao ◽  
Abdulaziz Alofi ◽  
Abdullah AL-Mazrooei ◽  
Ahmed Elaiw
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Varying ◽  
Time Varying Delay ◽  
Switched Neural Networks ◽  
Finite Time Boundedness ◽  
Varying Delay

scholarly journals Robust Finite-time Boundedness of Discrete-time Neural Networks with Time-varying Delays

2021 ◽  
Vol 17 ◽  
pp. 146-155
Author(s):  
Mengying Ding ◽  
Yali Dong
Keyword(s):  
Neural Networks ◽  
Discrete Time ◽  
Finite Time ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Time Varying ◽  
Finite Time Stability ◽  
Time Varying Delay ◽  
Finite Time Boundedness ◽  
Varying Delay

This paper is concerned with the problem of robust finite-time boundedness for the discrete-time neural networks with time-varying delays. By constructing an appropriate Lyapunov-Krasovskii functional, we propose the sufficient conditions which ensure the robust finite-time boundedness of the discrete-time neural networks with time-varying delay in terms of linear matrix inequalities. Then the sufficient conditions of robust finite-time stability for the discrete-time neural networks with time-varying delays are given. Finally, a numerical example is presented to illustrate the efficiency of proposed methods.

scholarly journals Finite-time Stabilization for Uncertain Neural Networks With Time-varying Delay

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Sufficient Conditions ◽  
Control Design ◽  
Time Varying ◽  
Time Varying Delay ◽  
The Neural Networks ◽  
Finite Time Boundedness ◽  
And Control ◽  
Varying Delay

In this paper, the problems of finite-time boundedness and control design for uncertain neuralnetworks with time-varying delay is considered. By constructing Lyapunov-Krasovskii function and using thematrix inequality method, sufficient conditions for finite-time boundedness of a class of neural networks withtime-varying delay are established. Then, we proposed a criterion to ensure that the neural networks with timevarying delay is finite-time stabilizable. A numerical example is given to verify the validity of the results.

Sign in / Sign up

Export Citation Format

Share Document