Corpus ID: 12816905

Recoverability of Group Sparse Signals from Corrupted Measurements via Robust Group Lasso

@article{Wei2015RecoverabilityOG,
  title={Recoverability of Group Sparse Signals from Corrupted Measurements via Robust Group Lasso},
  author={Xiaohan Wei and Qing Ling and Zhu Han},
  journal={ArXiv},
  year={2015},
  volume={abs/1509.08490}
}
This paper considers the problem of recovering a group sparse signal matrix $\mathbf{Y} = [\mathbf{y}_1, \cdots, \mathbf{y}_L]$ from sparsely corrupted measurements $\mathbf{M} = [\mathbf{A}_{(1)}\mathbf{y}_{1}, \cdots, \mathbf{A}_{(L)}\mathbf{y}_{L}] + \mathbf{S}$, where $\mathbf{A}_{(i)}$'s are known sensing matrices and $\mathbf{S}$ is an unknown sparse error matrix. A robust group lasso (RGL) model is proposed to recover $\mathbf{Y}$ and $\mathbf{S}$ through simultaneously minimizing the… Expand
Robust group LASSO over decentralized networks
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 itsExpand

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