AN EXTENDED BLOCK RESTRICTED ISOMETRY PROPERTY FOR SPARSE RECOVERY WITH NON-GAUSSIAN NOISE

• 来源期刊: 计算数学（英文版）
• 年，卷（期）: 2020,（6）
• 页码范围: 827-838
• 页数: 12页
• 语种: 英文
• DOI: 10.4208/jcm.1905-m2018-0256

摘要

We study the recovery conditions of weighted mixed l2/lp minimization for block sparse signal reconstruction from compressed measurements when partial block support information is available.We show theoretically that the extended block restricted isometry property can ensure robust recovery when the data fidelity constraint is expressed in terms of an lq norm of the residual error,thus establishing a setting wherein we are not restricted to Gaussian measurement noise.We illustrate the results with a series of numerical experiments.