Unconstrained Regularized lp-Norm Based Algorithm for the Reconstruction of Sparse Signals

被引：0
|
作者：
Pant, Jeevan K. [1 ]
Lu, Wu-Sheng [1 ]
Antoniou, Andreas [1 ]
机构：
[1] Univ Victoria, Dept Elect & Comp Engn, Victoria, BC V8W 3P6, Canada
来源：
2011 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2011年
关键词：
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 new algorithm for signal reconstruction in a compressive sensing framework is presented. The algorithm is based on minimizing an unconstrained regularized l(p) norm with p < 1 in the null space of the measurement matrix. The unconstrained optimization involved is performed by using a quasi-Newton algorithm in which a new line search based on Banach's fixed-point theorem is used. Simulation results are presented, which demonstrate that the proposed algorithm yields improved reconstruction performance and requires a reduced amount of computation relative to several known algorithms.
引用
收藏
页码：1740 / 1743
页数：4
相关论文
共 50 条
  • [1] ON lP-NORM SPARSE BLIND DECONVOLUTION
    Nose-Filho, Kenji
    Romano, Joao M. T.
    2014 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2014,
  • [2] Sparse Data Reconstruction via Adaptive lp-norm and Multilayer NMF
    Salehani, Yaser Esmaeili
    Gazor, Saeed
    7TH IEEE ANNUAL INFORMATION TECHNOLOGY, ELECTRONICS & MOBILE COMMUNICATION CONFERENCE IEEE IEMCON-2016, 2016,
  • [3] Adaptive lp-norm regularized sparse representation for human activity recognition in coal mines
    Wang D.
    Geng Z.
    Wang, Deyong (2548@pdsu.edu.cn), 1600, International Information and Engineering Technology Association (53): : 499 - 504
  • [4] Sparse-Representation-Based Direct Minimum Lp-Norm Algorithm for MRI Phase Unwrapping
    He, Wei
    Xia, Ling
    Liu, Feng
    COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2014, 2014
  • [5] Robust and Sparse Tensor Analysis with Lp-norm Maximization
    Tang, Ganyi
    Lu, Guifu
    Wang, Zhongqun
    PROCEEDINGS OF 2017 8TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2017), 2017, : 751 - 756
  • [6] A new weighted lp-norm for sparse hyperspectral unmixing
    Salehani, Yaser Esmaeili
    Gazor, Saeed
    Cheriet, Mohamed
    2017 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2017), 2017, : 1255 - 1259
  • [7] Conditional Sparse lp-norm Regression With Optimal Probability
    Hainline, John
    Juba, Brendan
    Le, Hai S.
    Woodruff, David P.
    22ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 89, 2019, 89
  • [8] Smoothing inertial neurodynamic approach for sparse signal reconstruction via Lp-norm minimization
    Zhao, You
    Liao, Xiaofeng
    He, Xing
    Tang, Rongqiang
    Deng, Weiwei
    NEURAL NETWORKS, 2021, 140 : 100 - 112
  • [9] Lp-norm based minimisation algorithm for signal parameter estimation
    Zhang, H
    Peng, YL
    ELECTRONICS LETTERS, 1999, 35 (20) : 1704 - 1705
  • [10] Reweighted lp-norm constraint least exponentiated square algorithm for sparse system identification
    Luo, Zhengyan
    Zhao, Haiquan
    Fang, Zian
    2018 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATIONS AND COMPUTING (ICSPCC), 2018,
12345