Sequentially Designed Compressed Sensing

被引:0
作者
Haupt, Jarvis [1 ]
Baraniuk, Richard [2 ]
Castro, Rui [3 ]
Nowak, Robert [4 ]
机构
[1] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN 55455 USA
[2] Rice Univ, Dept Elect & Comp Engn, Houston, TX 77005 USA
[3] Eindhoven Univ Technol, Dept Math, Eindhoven, Netherlands
[4] Univ Wisconsin, Dept Elect & Comp Engn, Madison, WI 53706 USA
来源
2012 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP) | 2012年
关键词
Adaptive sensing; compressed sensing; support recovery; RECOVERY;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A sequential adaptive compressed sensing procedure for signal support recovery is proposed and analyzed. The procedure is based on the principle of distilled sensing, and makes used of sparse sensing matrices to perform sketching observations able to quickly identify irrelevant signal components. It is shown that adaptive compressed sensing enables recovery of weaker sparse signals than those that can be recovered using traditional non-adaptive compressed sensing approaches.
引用
收藏
页码:401 / 404
页数:4
相关论文
共 50 条
  • [41] Foveated Compressed Sensing
    Ciocoiu, Iulian B.
    [J]. CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2015, 34 (03) : 1001 - 1015
  • [42] UNSCENTED COMPRESSED SENSING
    Carmi, Avishy Y.
    Mihaylova, Lyudmila
    Kanevsky, Dimitri
    [J]. 2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2012, : 5249 - 5252
  • [43] The Geometry of Off-the-Grid Compressed Sensing
    Poon, Clarice
    Keriven, Nicolas
    Peyre, Gabriel
    [J]. FOUNDATIONS OF COMPUTATIONAL MATHEMATICS, 2023, 23 (01) : 241 - 327
  • [44] Adaptive Matrix Design for Boosting Compressed Sensing
    Mangia, Mauro
    Pareschi, Fabio
    Rovatti, Riccardo
    Setti, Gianluca
    [J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2018, 65 (03) : 1016 - 1027
  • [45] Deterministic Compressed Sensing of heart sound signals
    Daponte, Pasquale
    De Vito, Luca
    Iadarola, Grazia
    Picariello, Francesco
    Rapuano, Sergio
    [J]. 2021 IEEE INTERNATIONAL SYMPOSIUM ON MEDICAL MEASUREMENTS AND APPLICATIONS (IEEE MEMEA 2021), 2021,
  • [46] Statistical Compressed Sensing of Gaussian Mixture Models
    Yu, Guoshen
    Sapiro, Guillermo
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2011, 59 (12) : 5842 - 5858
  • [47] A Decentralized Reconstruction Algorithm for Distributed Compressed Sensing
    Xu, Wenbo
    Cui, Yupeng
    Li, Zhilin
    Lin, Jiaru
    [J]. WIRELESS PERSONAL COMMUNICATIONS, 2017, 96 (04) : 6175 - 6182
  • [48] A Combination Approach for Compressed Sensing Signal Reconstruction
    Zhang, Yujie
    Qi, Rui
    Zeng, Yanni
    [J]. FIRST INTERNATIONAL WORKSHOP ON PATTERN RECOGNITION, 2016, 0011
  • [49] Making Do with Less: An Introduction to Compressed Sensing
    Bryan, Kurt
    Leise, Tanya
    [J]. SIAM REVIEW, 2013, 55 (03) : 547 - 566
  • [50] Compressed Sensing of Digital Signals with Finite Alphabets
    Xing, Zhengli
    Zhou, Jie
    Ye, Liangfeng
    Yan, Lun
    Li, Bing
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION PROBLEM-SOLVING (ICCP), 2015, : 211 - 214