Sparse recovery on Euclidean Jordan algebras

被引:3
|
作者
Kong, Lingchen [1 ]
Sun, Jie [2 ,3 ]
Tao, Jiyuan [4 ]
Xiu, Naihua [1 ]
机构
[1] Beijing Jiaotong Univ, Dept Appl Math, Beijing 100044, Peoples R China
[2] Natl Univ Singapore, Dept Decis Sci, Singapore 117548, Singapore
[3] Curtin Univ, Dept Math & Stat, Bentley, WA, Australia
[4] Loyola Univ Maryland, Dept Math & Stat, Baltimore, MD 21210 USA
基金
中国国家自然科学基金;
关键词
Sparse recovery on Euclidean Jordan algebra; Nuclear norm minimization; Restricted isometry property; Null space property; s-goodness; Exact and stable recovery; SMOOTHING NEWTON METHOD; LINEAR TRANSFORMATIONS; MATRIX EQUATIONS; SIGNAL RECOVERY; P-PROPERTIES;
D O I
10.1016/j.laa.2014.09.018
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper is concerned with the problem of sparse recovery on Euclidean Jordan algebra (SREJA), which includes the sparse signal recovery problem and the low-rank symmetric matrix recovery problem as special cases. We introduce the notions of restricted isometry property (RIP), null space property (NSF), and s-goodness for linear transformations in s-SREJA, all of which provide sufficient conditions for s-sparse recovery via the nuclear norm minimization on Euclidean Jordan algebra. Moreover, we show that both the s-goodness and the NSF are necessary and sufficient conditions for exact s-sparse recovery via the nuclear norm minimization on Euclidean Jordan algebra. Applying these characteristic properties, we establish the exact and stable recovery results for solving SREJA problems via nuclear norm minimization. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:65 / 87
页数:23
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