Autor:	Wang, Manxi, Li, Yongcheng, Wei, Xiaohan, Ling, Qing
Rok vydání:	2017
Předmět:	Computer Science - Distributed Parallel and Cluster Computing
Druh dokumentu:	Working Paper
Popis:	This paper considers the recovery of group sparse signals over a multi-agent network, where the measurements are subject to sparse errors. We first investigate the robust group LASSO model and its centralized algorithm based on the alternating direction method of multipliers (ADMM), which requires a central fusion center to compute a global row-support detector. To implement it in a decentralized network environment, we then adopt dynamic average consensus strategies that enable dynamic tracking of the global row-support detector. Numerical experiments demonstrate the effectiveness of the proposed algorithms. Comment: IEEE GlobalSIP 2016
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1701.03043 Zobrazit plný text záznamu View this record from Arxiv