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arXiv · 1907.09442

Block-sparse Recovery of Semidefinite Systems and Generalized Null Space Conditions

Janin Heuer·Frederic Matter·Marc E. Pfetsch·Thorsten Theobald
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Abstract

This article considers the recovery of low-rank matrices via a convex nuclear-norm minimization problem and presents two null space properties (NSP) which characterize uniform recovery for the case of block-diagonal matrices and block-diagonal positive semidefinite matrices. These null-space conditions turn out to be special cases of a new general setup, which allows to derive the mentioned NSPs and well-known NSPs from the literature. We discuss the relative strength of these conditions and also present a deterministic class of matrices that satisfies the block-diagonal semidefinite NSP.

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Janin Heuer, Frederic Matter, Marc E. Pfetsch, Thorsten Theobald. 2019-07-22. Block-sparse Recovery of Semidefinite Systems and Generalized Null Space Conditions. https://arxiv.org/abs/1907.09442

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