Exponential synchronization of coupled memristive neural networks via pinning control

被引:0
|
作者
王冠 [1 ,2 ]
沈轶 [1 ,2 ]
尹泉 [1 ,2 ]
机构
[1] Department of Control Science and Engineering, Huazhong University of Science and Technology
[2] Key Laboratory of Ministry of Education for Image Processing and Intelligent Control
基金
中国国家自然科学基金;
关键词
synchronization; memristor; coupled neural networks; pinning control;
D O I
暂无
中图分类号
TP13 [自动控制理论]; TP183 [人工神经网络与计算];
学科分类号
0711 ; 071102 ; 0811 ; 081101 ; 081103 ; 081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper is concerned with the exponential synchronization problem of coupled memristive neural networks. In contrast to general neural networks, memristive neural networks exhibit state-dependent switching behaviors due to the physical properties of memristors. Under a mild topology condition, it is proved that a small fraction of controlled sub-systems can efficiently synchronize the coupled systems. The pinned subsystems are identified via a search algorithm. Moreover, the information exchange network needs not to be undirected or strongly connected. Finally, two numerical simulations are performed to verify the usefulness and effectiveness of our results.
引用
收藏
页码:207 / 216
页数:10
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