Performance Evaluation of Finite Sparse Signals for Compressed Sensing Frameworks

被引：1
|
作者：
Seong, Jin-Taek [1 ]
机构：
[1] Honam Univ, Dept Informat & Commun Engn, Gwangju, South Korea
来源：
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2018年 / E101D卷 / 02期
基金：
新加坡国家研究基金会;
关键词：
compressed sensing; finite fields; signal recovery; probabilistic decoding; ABSOLUTE-VALUES OPTIMIZATION; SUM; RECOVERY;
D O I：
10.1587/transinf.2017EDL8166
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we consider to develop a recovery algorithm of a sparse signal for a compressed sensing (CS) framework over finite fields. A basic framework of CS for discrete signals rather than continuous signals is established from the linear measurement step to the reconstruction. With predetermined priori distribution of a sparse signal, we reconstruct it by using a message passing algorithm, and evaluate the performance obtained from simulation. We compare our simulation results with the theoretic bounds obtained from probability analysis.
引用
收藏
页码：531 / 534
页数：4
相关论文
共 50 条
  • [1] On the performance comparison of compressed sensing based detectors for sparse signals Compressive detectors for sparse signals
    Anupama, R.
    Jattimath, Siddeshwar M.
    Shruthi, B. M.
    Sure, Pallaviram
    [J]. 2014 INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRONICS, COMPUTERS AND COMMUNICATIONS (ICAECC), 2014,
  • [2] Compressed sensing of approximately sparse signals
    Stojnic, Mihailo
    Xu, Weiyu
    Hassibi, Babak
    [J]. 2008 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS, VOLS 1-6, 2008, : 2182 - +
  • [3] Performance Bounds of Compressed Sensing Recovery Algorithms for Sparse Noisy Signals
    Li, Xiangling
    Cui, Qimei
    Tao, Xiaofeng
    Yang, Xianjun
    Rehman, Waheed Ur
    Guo, Y. Jay
    [J]. 2013 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2013, : 2884 - 2889
  • [4] Explicit Constructions for Compressed Sensing of Sparse Signals
    Indyk, Piotr
    [J]. PROCEEDINGS OF THE NINETEENTH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS, 2008, : 30 - 33
  • [5] Compressed Sensing Reconstruction of Convolved Sparse Signals
    Tsagkatakis, Grigorios
    Tsakalides, Panagiotis
    Woiselle, Arnaud
    Bousquet, Marc
    Tzagkarakis, George
    Starck, Jean-Luc
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2014,
  • [6] Adaptive Compressed Sensing for Sparse Signals in Noise
    Iwen, M. A.
    Tewfik, A. H.
    [J]. 2011 CONFERENCE RECORD OF THE FORTY-FIFTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS (ASILOMAR), 2011, : 1240 - 1244
  • [7] Distributed compressed sensing of jointly sparse signals
    Duarte, Marco F.
    Sarvotham, Shriram
    Baron, Dror
    Wakin, Michael B.
    Baraniuk, Richard G.
    [J]. 2005 39th Asilomar Conference on Signals, Systems and Computers, Vols 1 and 2, 2005, : 1537 - 1541
  • [8] COMPRESSED SENSING FOR BLOCK-SPARSE SMOOTH SIGNALS
    Gishkori, Shahzad
    Leus, Geert
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2014,
  • [9] GREEDY PURSUITS FOR COMPRESSED SENSING OF JOINTLY SPARSE SIGNALS
    Sundman, Dennis
    Chatterjee, Saikat
    Skoglund, Mikael
    [J]. 19TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO-2011), 2011, : 368 - 372
  • [10] Distributed Compressed Sensing for Block-sparse Signals
    Wang, Xing
    Guo, Wenbin
    Lu, Yang
    Wang, Wenbo
    [J]. 2011 IEEE 22ND INTERNATIONAL SYMPOSIUM ON PERSONAL INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC), 2011, : 695 - 699
12345