PROMP: A sparse recovery approach to lattice-valued signals

被引:10
作者
Flinth, Axel [1 ]
Kutyniok, Gitta [1 ]
机构
[1] Tech Univ Berlin, Inst Math, Str 17 Juni 136, D-10623 Berlin, Germany
关键词
Compressed sensing; Basis pursuit; Lattice search; Orthogonal matching pursuit; High-dimensional geometry; MINIMIZATION;
D O I
10.1016/j.acha.2016.12.004
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Applications such as wireless communications require efficient sensing techniques of signals with the a priori knowledge of those being lattice-valued. In this paper, we study the impact of this prior information on compressed sensing methodologies, and introduce and analyze PROMP ("PReprojected Orthogonal Matching Pursuit") as a novel algorithmic approach for sparse recovery of lattice-valued signals. More precisely, we first show that the straightforward approach to project the solution of Basis Pursuit onto a prespecified lattice does not improve the performance of Basis Pursuit in this situation. We then introduce PROMP as a novel sparse recovery algorithm for lattice-valued signals which has very low computational complexity, alongside a detailed mathematical analysis of its performance and stability under noise. Finally, we present numerical experiments which show that PROMP outperforms standard sparse recovery approaches in the lattice-valued signal regime. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:668 / 708
页数:41
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