Robust multi-task distributed estimation based on generalized maximum correntropy criterion  

作　　者：胡倩 陈枫 叶明 Qian Hu;Feng Chen;Ming Ye(College of Artificial Intelligence,Southwest University,Chongqing 400715,China)

机构地区：[1]College of Artificial Intelligence,Southwest University,Chongqing 400715,China

出　　处：《Chinese Physics B》2023年第6期705-715,共11页中国物理B（英文版）

摘　　要：False data injection(FDI) attacks are common in the distributed estimation of multi-task network environments, so an attack detection strategy is designed by combining the generalized maximum correntropy criterion. Based on this, we propose a diffusion least-mean-square algorithm based on the generalized maximum correntropy criterion(GMCC-DLMS)for multi-task networks. The algorithm achieves gratifying estimation results. Even more, compared to the related work,it has better robustness when the number of attacked nodes increases. Moreover, the assumption about the number of attacked nodes is relaxed, which is applicable to multi-task environments. In addition, the performance of the proposed GMCC-DLMS algorithm is analyzed in the mean and mean-square senses. Finally, simulation experiments confirm the performance and effectiveness against FDI attacks of the algorithm.

关 键 词：distributed estimation generalized correntropy multi-task networks adaptive filtering 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置] TN915.08[自动化与计算机技术—控制科学与工程]