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Identifiability for Gauge Regularizations and Algorithms for Block-Sparse Synthesis in Compressive Sensing

机译:压缩传感中量规正则化的可识别性和块稀疏综合的算法

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In the paper we give a characterization of identifiability for regularizations with gauges of compact convexes. This extends the classic identifiability results from the standard l1-regularization framework in compressive sensing. We show that the standard dual certificate techniques can no longer work by themselves ouside the polytope case. We then apply the general characterization to the caseof block-sparse regularizations and obtain an identification algorithm based on a combination of the standard duality and a convex-projection technique.
机译:在本文中,我们给出了具有紧凑凸度规的正则化的可识别性表征。这扩展了压缩感测中标准l1-regularization框架的经典可识别性结果。我们表明,标准的双证书技术不能再自行取代多面体案件。然后,将一般特征应用于块稀疏正则化的情况,并基于标准对偶性和凸投影技术的组合获得识别算法。

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