论文标题
部分可观测时空混沌系统的无模型预测
Dynamic Event-Triggered Discrete-Time Linear Time-Varying System with Privacy-Preservation
论文作者
论文摘要
本文着重于具有隐私保护的离散时间无线传感器网络。在实际应用中，传感器之间的信息交换受到攻击。对于信息传输过程中攻击引起的信息泄漏，引入了系统状态的隐私保护。为了使通信资源更有效地利用，设计了一个动态事件触发的设置会员估计器。此外，对系统的隐私进行了分析，以确保真实数据的安全性。结果，使用递归凸优化分析具有差异隐私的设置会员估计器。然后研究了系统的稳态性能。最后，提出了一个示例，以证明包含隐私分析的提议的分布式过滤器的可行性。
This paper focuses on discrete-time wireless sensor networks with privacy-preservation. In practical applications, information exchange between sensors is subject to attacks. For the information leakage caused by the attack during the information transmission process, privacy-preservation is introduced for system states. To make communication resources more effectively utilized, a dynamic event-triggered set-membership estimator is designed. Moreover, the privacy of the system is analyzed to ensure the security of the real data. As a result, the set-membership estimator with differential privacy is analyzed using recursive convex optimization. Then the steady-state performance of the system is studied. Finally, one example is presented to demonstrate the feasibility of the proposed distributed filter containing privacy-preserving analysis.
