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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Vydané v:	Signal processing Ročník 202
Hlavný autor:	Zhou, Zhiyong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.01.2023
Predmet:	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
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