Exponential synchronization of chaotic systems with stochastic noise via periodically intermittent control

2020 ◽  
Vol 30 (7) ◽  
pp. 2611-2624 ◽  
Author(s):  
Cong Xu ◽  
Dongbing Tong ◽  
Qiaoyu Chen ◽  
Wuneng Zhou ◽  
Yuhua Xu
Author(s):  
Qing Ding ◽  
Yinfang Song

This paper deals with the exponential synchronization problem of inertial Cohen–Grossberg neural networks with time-varying delays under periodically intermittent control. In light of Lyapunov–Krasovskii functional method and inequality techniques, some sufficient conditions are attained to ensure the exponential synchronization of the master-slave system on the basis of p-norm. Meanwhile, the periodically intermittent control schemes are designed. Finally, in order to verify the effectiveness of theoretical results, some numerical simulations are provided.


2014 ◽  
Vol 07 (02) ◽  
pp. 1450017
Author(s):  
Pinghua Yang ◽  
Xinan Tang

This paper deals with exponential synchronization for a class of neural networks with mixed time-varying delays via periodically intermittent control. Some novel and effective exponential synchronization criteria are derived by constructing Lyapunov functional and applying some analysis techniques. These results presented in this paper generalize and improve many known results. Finally, this paper presents an illustrative example and uses the simulated results to show the feasibility and effectiveness of the proposed scheme.


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