Improved global asymptotically stability of cellular neural networks with time-varying delay

2011 ◽  
Author(s):  
Wenxia Du ◽  
Xueli Wu
Keyword(s):  
Neural Networks ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Time Varying Delay ◽  
Varying Delay ◽  
Global Asymptotically Stability

Mean-Square Exponential Stability of Stochastic Interval Cellular Neural Networks with Time-Varying Delay

2013 ◽  
Vol 760-762 ◽  
pp. 1742-1747
Author(s):  
Jin Fang Han
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Mean Square ◽  
Razumikhin Theorem ◽  
Time Varying Delay ◽  
Mean Square Exponential Stability ◽  
The Mean ◽  
Varying Delay

This paper is concerned with the mean-square exponential stability analysis problem for a class of stochastic interval cellular neural networks with time-varying delay. By using the stochastic analysis approach, employing Lyapunov function and norm inequalities, several mean-square exponential stability criteria are established in terms of the formula and Razumikhin theorem to guarantee the stochastic interval delayed cellular neural networks to be mean-square exponential stable. Some recent results reported in the literatures are generalized. A kind of equivalent description for this stochastic interval cellular neural networks with time-varying delay is also given.

Stability of cellular neural networks with time-varying delay

2003 ◽  
Vol 50 (5) ◽  
pp. 677-679 ◽  
Author(s):  
Gwo-Jeng Yu ◽  
Chien-Yu Lu ◽  
J.S. Tsai ◽  
Te-Jen Su ◽  
Bin-Da Liu
Keyword(s):  
Neural Networks ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Time Varying Delay ◽  
Varying Delay

Stability of cellular neural networks with time varying delay

2010 ◽  
Vol 9 (1/2) ◽  
pp. 59 ◽  
Author(s):  
Jian hua Zhang ◽  
Hui guang Li ◽  
Xin ping Guan ◽  
Xue li Wu
Keyword(s):  
Neural Networks ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Time Varying Delay ◽  
Varying Delay

IMPROVED ROBUST STABILITY CRITERION FOR UNCERTAIN CELLULAR NEURAL NETWORKS WITH TIME-VARYING DELAY

2010 ◽  
Vol 24 (04n05) ◽  
pp. 503-511 ◽  
Author(s):  
S. M. LEE
Keyword(s):  
Neural Networks ◽  
Robust Stability ◽  
Stability Criterion ◽  
Nonlinear Function ◽  
Cellular Neural Networks ◽  
Linear Matrix ◽  
Time Varying ◽  
Time Varying Delay ◽  
Robust Stability Analysis ◽  
Varying Delay

In this paper, we propose a new robust stability analysis method for uncertain cellular neural networks with time-varying delay. The proposed stability criterion is based on the Lyapunov function with sector bounded nonlinear function. The sufficient condition for the stability is derived in terms of LMI (linear matrix inequality). Numerical examples show the effectiveness of the proposed method.

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