A new sufficient condition for sparse vector recovery via ℓ1 − ℓ2 local minimization

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2021-04-10 DOI:10.1142/S0219530521500068
Ning Bi, J. Tan, Wai-Shing Tang
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引用次数: 2

Abstract

In this paper, we provide a necessary condition and a sufficient condition such that any [Formula: see text]-sparse vector [Formula: see text] can be recovered from [Formula: see text] via [Formula: see text] local minimization. Moreover, we further verify that the sufficient condition is naturally valid when the restricted isometry constant of the measurement matrix [Formula: see text] satisfies [Formula: see text]. Compared with the existing [Formula: see text] local recoverability condition [Formula: see text], this result shows that [Formula: see text] local recoverability contains more measurement matrices.
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给出了稀疏向量通过1 ~ 2局部极小化恢复的一个新的充分条件
在本文中,我们提供了一个必要条件和一个充分条件,使得任何[公式:见文本]-稀疏向量[公式:看文本]都可以通过[公式:见图文本]局部最小化从[公式:可见文本]中恢复。此外,我们进一步验证了当测量矩阵[公式:见正文]的受限等距常数满足[公式:看正文]时,充分条件自然有效。与现有的[公式:见正文]局部可恢复性条件[公式:见图正文]相比,该结果表明[公式:看正文]局部的可恢复性包含了更多的测量矩阵。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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