作者
Wangli He, Tinghui Luo, Yang Tang, Wenli Du, Yu-Chu Tian, Feng Qian
发表日期
2019/10/17
期刊
IEEE transactions on neural networks and learning systems
卷号
31
期号
9
页码范围
3334-3345
出版商
IEEE
简介
This article presents a secure communication scheme based on the quantized synchronization of master-slave neural networks under an event-triggered strategy. First, a dynamic event-triggered strategy is proposed based on a quantized output feedback, for which a quantized output feedback controller is formed. Second, theoretical criteria are derived to ensure the bounded synchronization of master-slave neural networks. With these criteria, an explicit upper bound is given for the synchronization error. Sufficient conditions are also provided on the existence of quantized output feedback controllers. A Chua's circuit is chosen to illustrate the effectiveness of our theoretical results. Third, a secure communication scheme is presented based on the synchronization of master-slave neural networks by combining the basic principle of cryptology. Then, a secure image communication is studied to verify the feasibility and …
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