RIP analysis for the weighted ℓr-ℓ1 minimization method

•The restricted isometry property (RIP) and high-order RIP analysis results for the weighted ℓr−ℓ1 minimization method are presented.•Through a novel decomposition of the objective function into a difference of two convex functions, the weighted ℓr−ℓ1 minimization problem is solved via the differenc...

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Bibliographic Details

Published in:	Signal processing Vol. 202
Main Author:	Zhou, Zhiyong
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.01.2023
Subjects:	Compressive sensing Difference of convex functions algorithms Nonconvex sparse recovery Restricted isometry property Weighted [formula omitted] minimization Compressive sensing Restricted isometry property Difference of convex functions algorithms Nonconvex sparse recovery Weighted ℓr−ℓ1 minimization
ISSN:	0165-1684
Online Access:	Get full text
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