New chaotic memristive cellular neural network and its application in secure communication system

被引:73
|
作者
Xiu, Chunbo [1 ,2 ]
Zhou, Ruxia [1 ,2 ]
Liu, Yuxia [3 ]
机构
[1] Tiangong Univ, Sch Elect Engn & Automat, Tianjin 300387, Peoples R China
[2] Tiangong Univ, Key Lab Adv Elect Engn & Energy Technol, Tianjin 300387, Peoples R China
[3] ShanDong Water Conservancy Vocat Coll, Dept Informat Engn, Rizhao 276826, Peoples R China
基金
中国国家自然科学基金;
关键词
Cellular neural network; Memristor; Chaos synchronization; Secure communication; Sliding mode control;
D O I
10.1016/j.chaos.2020.110316
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In order to improve the engineering feasibility of the memristive cellular neural network, a new memristor model with the smooth characteristic curve is designed. Based on the new memristor model, a new four-dimensional chaotic memristive cellular neural network (CNN) system is constructed, and its chaotic dynamic behaviors are analyzed. It can be applied to the secure communication based on the chaos synchronization control. Because both the external disturbances and uncertainties of internal parameters are maybe in the practical secure communication system, sliding mode control is used to perform the chaos synchronization between the sender and receiver. A new terminal sliding mode surface is designed to make the error system converge to zero in a finite time. Simulation results show that the new terminal sliding mode control has good robustness to the external disturbances and uncertainties of internal parameters, and the new chaotic memristive CNN system can be used in the secure communication by the chaos synchronization based on sliding mode control. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:15
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