Implementation of l1 Magic and One bit Compressed Sensing based on Linear Programming Using Excel

被引：1
|
作者：
Indukala, P. K. [1 ]
Lakshmi, K. [1 ]
Sowmya, V [1 ]
Soman, K. P. [1 ]
机构：
[1] Amrita Vishwa Vidyapeetham, Ctr Excellence Computat Engn & Networking, Amrita Sch Engn, Coimbatore 641112, Tamil Nadu, India
来源：
2012 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING AND COMMUNICATIONS (ICACC) | 2012年
关键词：
Compressed sensing; l(1) Magic; One bit Compressed sensing; Linear Programming; Excel;
D O I：
10.1109/ICACC.2012.67
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Compressed sensing helps in the reconstruction of sparse or compressible signals from small number of measurements. The sparse representation has great importance in modern signal processing. The main objective is to provide a strong understanding of the concept behind the theory of compressed sensing by using the key ideas from linear algebra. In this paper, the concept of compressed sensing is explained through an experiment formulated based on linear programming and solved using l(1) magic and One bit compressed sensing methods in Excel.
引用
收藏
页码：69 / 72
页数：4
相关论文
共 50 条
  • [1] One-Bit Compressed Sensing by Linear Programming
    Plan, Yaniv
    Vershynin, Roman
    COMMUNICATIONS ON PURE AND APPLIED MATHEMATICS, 2013, 66 (08) : 1275 - 1297
  • [2] Characterization of l1 minimizer in one-bit compressed sensing
    Bi, Ning
    Tan, Jun
    ANALYSIS AND APPLICATIONS, 2019, 17 (06) : 1005 - 1021
  • [3] PHASE TRANSITIONS IN ERROR CORRECTING AND COMPRESSED SENSING BY l1 LINEAR PROGRAMMING
    Ashino, Ryuichi
    Vaillancourt, Remi
    INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING, 2013, 11 (04)
  • [4] l1 - lq (1 < q ≤ 2) Minimization for One-Bit Compressed Sensing
    Lu, Yancheng
    Bi, Ning
    Wan, Anhua
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2024, 72 : 2649 - 2662
  • [5] Compressed sensing based loss tomography using weighted l1 minimization
    Fan, XiaoBo
    Li, Xingming
    Zhang, JianKang
    COMPUTER COMMUNICATIONS, 2018, 127 : 122 - 130
  • [6] L1 RIP-Based Robust Compressed Sensing
    Gao, X.
    Zhou, J.
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2022, 41 (02) : 851 - 866
  • [7] One Scan 1-Bit Compressed Sensing
    Li, Ping
    ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 51, 2016, 51 : 1515 - 1523
  • [8] TOWARDS IMPROVING l1 OPTIMIZATION IN COMPRESSED SENSING
    Stojnic, Mihailo
    2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, : 3938 - 3941
  • [9] An Alternating l1 Approach to the Compressed Sensing Problem
    Chretien, Stephane
    IEEE SIGNAL PROCESSING LETTERS, 2010, 17 (02) : 181 - 184
  • [10] ONE-BIT COMPRESSED SENSING USING GENERATIVE MODELS
    Joseph, Geethu
    Katie, Swatantra
    Varshney, Pramod K.
    2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2020, : 3437 - 3441
12345