The Dantzig Selector: Sparse Signals Recovery via l_p-q Minimization

Fuente: arXiv
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Main Authors: Li, Jie, Deng, Chaohong, Li, Baode
Format: Preprint
Published: 2023
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author Li, Jie
Deng, Chaohong
Li, Baode
author_facet Li, Jie
Deng, Chaohong
Li, Baode
contents In the paper, we proposed the Dantzig selector based on the $l_{p-q}$ ($0<p\leq1, 1<q\leq2$) minimization for the signal recovery. First, we establish the convex combination representation of sparse vectors under the $l_{p-q}$ minimization problem. Next, we give the signal recovery guarantees that based on two classes of restricted isometry property frames. Last, some graphical illustrations are presented for the sufficient conditions of the signal recovery.
format Preprint
id arxiv_https___arxiv_org_abs_2309_00895
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle The Dantzig Selector: Sparse Signals Recovery via l_p-q Minimization
Li, Jie
Deng, Chaohong
Li, Baode
Optimization and Control
90C26, 94A12, 94A08
In the paper, we proposed the Dantzig selector based on the $l_{p-q}$ ($0<p\leq1, 1<q\leq2$) minimization for the signal recovery. First, we establish the convex combination representation of sparse vectors under the $l_{p-q}$ minimization problem. Next, we give the signal recovery guarantees that based on two classes of restricted isometry property frames. Last, some graphical illustrations are presented for the sufficient conditions of the signal recovery.
title The Dantzig Selector: Sparse Signals Recovery via l_p-q Minimization
topic Optimization and Control
90C26, 94A12, 94A08
url https://arxiv.org/abs/2309.00895