计算机科学
同步(交流)
记忆电阻器
人工神经网络
控制器(灌溉)
内容寻址存储器
人工智能
控制理论(社会学)
控制(管理)
频道(广播)
电子工程
计算机网络
农学
生物
工程类
作者
Manman Yuan,Xiong Luo,Ming Xue,Zhen Han,Lei Sun,Peican Zhu
标识
DOI:10.1016/j.chaos.2022.112311
摘要
Memristor-based bidirectional associative memory neural networks (MBAMNNs) analysis can help to reveal the dynamic basis of secure communication. Effectively representing the synchronization of MBAMNNs is the principal task of applying brain-inspired neural networks to image hiding. Previous research has typically utilized continuous control methods to represent the synchronization of MBAMNNs, but these are not well coordinated under limited network bandwidth. Besides, the special communication features and uncertainties of MBAMNNs will affect the image encryption/decryption by introducing the concept of chaos synchronization for image hiding, but few studies have explored such elements. To address these two issues, we propose an event-triggered hybrid impulsive scheme on lag synchronization for image hiding. Specifically, we incorporate both time-varying uncertainties and the multi-layer topology structure of MBAMNNs into a designed event-triggered scheme. The frequency of the controller can be automatically updated from two novel triggered conditions, and Zeno-behavior can be avoided effectively. Experimental results demonstrate that our scheme not only outperforms several exciting approaches in synchronization but also can effectively realize the image hiding under low energy consumption.
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