Sampled-Data Synchronization for Chaotic Neural Networks with Mixed Delays

Author(s):  
Rui-Xing Nie ◽  
Zhi-Yi Sun ◽  
Jian-An Wang ◽  
Yao Lu
2019 ◽  
Vol 346 ◽  
pp. 30-37 ◽  
Author(s):  
Hong-Hai Lian ◽  
Shen-Ping Xiao ◽  
Zhen Wang ◽  
Xiao-Hu Zhang ◽  
Hui-Qin Xiao

2017 ◽  
Vol 260 ◽  
pp. 25-31 ◽  
Author(s):  
Hong-Bing Zeng ◽  
Kok Lay Teo ◽  
Yong He ◽  
Honglei Xu ◽  
Wei Wang

2009 ◽  
Vol 23 (09) ◽  
pp. 1171-1187 ◽  
Author(s):  
YANG TANG ◽  
RUNHE QIU ◽  
JIAN-AN FANG

In this letter, a general model of an array of N linearly coupled chaotic neural networks with hybrid coupling is proposed, which is composed of constant coupling, time-varying delay coupling and distributed delay coupling. The complex network jumps from one mode to another according to a Markovian chain with known transition probability. Both the coupling time-varying delays and the coupling distributed delays terms are mode-dependent. By the adaptive feedback technique, several sufficient criteria have been proposed to ensure the synchronization in an array of jump chaotic neural networks with mode-dependent hybrid coupling and mixed delays in mean square. Finally, numerical simulations illustrated by mode switching between two complex networks of different structure dependent on mode switching verify the effectiveness of the proposed results.


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