MMV subspace pursuit (m-sp) algorithm for joint sparse multiple measurement vectors recovery - 文章详情页

作者：

Liu, Sujuan (Liu, Sujuan.) | Zheng, Lili (Zheng, Lili.) | Liu, Lei (Liu, Lei.) | Lin, Qianjin (Lin, Qianjin.)

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摘要：

In　this　paper,　MMV　Subspace　Pursuit　(M-SP)　algorithm　is　proposed　for　solving　joint　sparse　multiple　measurement　vectors　(MMV)　problem.　The　pre-selection　and　backtracking　mechanisms　are　used　in　M-SP,　so　M-SP　not　only　has　higher　recovery　performance　than　some　existing　algorithms,　but　also　significantly　reduces　the　iteration　number　for　improving　the　signal　recovery　efficiency.　Simulations　results　show　that　M-SP　and　Simultaneous　Compressive　Sampling　Matching　Pursuit　(SCoSaMP)　have　almost　identical　recovery　performance　and　iteration　times,　but　M-SP　significantly　reduces　the　computation　complexity　in　per　iteration.　For　example,　when　sparsity　K　is　5,　the　computational　complexity　of　M-SP　is　24.0%　of　that　of　SCoSaMP　in　each　iteration.　©　2019　IEEE.

关键词：

Vectors Recovery Signal reconstruction Iterative methods

作者机构：

[ 1 ] [Liu, Sujuan]School of Microelectronics, Beijing University of Technology, Beijing; 100124, China
[ 2 ] [Zheng, Lili]School of Microelectronics, Beijing University of Technology, Beijing; 100124, China
[ 3 ] [Liu, Lei]School of Microelectronics, Beijing University of Technology, Beijing; 100124, China
[ 4 ] [Lin, Qianjin]School of Microelectronics, Beijing University of Technology, Beijing; 100124, China

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