 New chaotic memristive cellular neural network and its application in secure communication systemChunbo Xiu, Ruxia Zhou and Yuxia Liu Chaos, Solitons & Fractals, 2020, vol. 141, issue C Abstract: 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. Keywords: Cellular neural network; Memristor; Chaos synchronization; Secure communication; Sliding mode control (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:141:y:2020:i:c:s0960077920307128 DOI: 10.1016/j.chaos.2020.110316 Access Statistics for this article Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros More articles in Chaos, Solitons & Fractals from Elsevier |
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