On the \(\ell_1\)-norm invariant convex \(k\)-sparse decomposition of signals

DOI10.1007/s40305-013-0030-yzbMath1310.94030arXiv1305.6021OpenAlexW2071392157MaRDI QIDQ743785

Guangwu Xu, Zhiqiang Xu

Publication date: 30 September 2014

Published in: Journal of the Operations Research Society of China (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1305.6021

zbMATH Keywords

sparse recoveryrestricted isometry property\(\ell_1\) minimizationconvex \(k\)-sparse decomposition

Mathematics Subject Classification ID

Nonlinear programming (90C30) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

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Cites Work

• Sharp RIP bound for sparse signal and low-rank matrix recovery
• Decoding by Linear Programming
• Compressed Sensing and Affine Rank Minimization Under Restricted Isometry
• New Bounds for Restricted Isometry Constants
• Stable Recovery of Sparse Signals and an Oracle Inequality
• Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-Rank Matrices