Rapid compressed sensing reconstruction: a semi-tensor product approach
type: Item
instance of: scholarly article
title: Rapid compressed sensing reconstruction: a semi-tensor product approach
zbMATH Open document ID: 1456.94011
author: Jin-Ming Wang
author: Zhangquan Wang
author: Sen Xu
author: Jun Jiang
author: Zhenyu Xu
published in: Information Sciences
publication date: 2021-03-18T00:00:00Z
Mathematics Subject Classification ID: 94A08
zbMATH DE Number: 7325070
zbMATH Keywords: compressed sensing
zbMATH Keywords: semi-tensor product
zbMATH Keywords: parallel reconstruction
zbMATH Keywords: random measurement matrix
zbMATH Keywords: rapid reconstruction
zbMATH Keywords: storage space
describes a project that uses: CoSaMP
MaRDI profile type: Publication
full work available at URL: j.ins.2019.09.071
OpenAlex ID: W2978752610
cites work: Deterministic Construction of Binary, Bipolar, and Ternary Compressed Sensing Matrices
cites work: A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
cites work: Enhancing sparsity by reweighted \(\ell _{1}\) minimization
cites work: Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
cites work: Analysis and control of Boolean networks. A semi-tensor product approach.
cites work: Q3224871
cites work: Q5399977
cites work: Iteratively reweighted least squares minimization for sparse recovery
cites work: Compressed sensing
cites work: Kronecker Compressive Sensing
cites work: Optimized Projections for Compressed Sensing
cites work: CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
cites work: A Compressed Sensing Approach to Block-Iterative Equalizers
cites work: Subspace Pursuit for Compressive Sensing Signal Reconstruction
cites work: Accelerating Overrelaxed and Monotone Fast Iterative Shrinkage-Thresholding Algorithms With Line Search for Sparse Reconstructions
Wikidata QID: Q127187534
DOI: 10.1016/J.INS.2019.09.071
description: scientific article; zbMATH DE number 7325070