A Self-adaptive Proximal Point Algorithm for Signal Reconstruction in Compressive Sensing

被引：0

作者：

Huai, Kaizhan ^{[1
]}

Li, Yejun ^{[2
]}

Ni, Mingfang ^{[1
]}

Yu, Zhanke ^{[1
]}

Wang, Xiaoguo ^{[1
]}

机构：

[1] PLA Univ Sci & Technol, Inst Commun Engn, Nanjing, Jiangsu, Peoples R China

[2] Xian Commun Inst, Xian, Shaanxi, Peoples R China

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP) | 2016年

关键词：

compressive sensing; signal reconstruction; proximal point algorithm; self-adaptive; PURSUIT;

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：

Compressive sensing (CS) is a new framework for simulations sensing and compressive. How to reconstruct a sparse signal from limited measurements is the key problem in CS. For solving the reconstruction problem of a sparse signal, we proposed a self-adaptive proximal point algorithm (PPA). This algorithm can handle the sparse signal reconstruction by solving a substituted problem-l(1) problem. At last, the numerical results shows that the proposed method is more effective compared with the compressive sampling matching pursuit (CoSaMP).

引用

页码：389 / 393

页数：5

共 50 条

[31] Self-Adaptive Wolf Search Algorithm
Song, Qun
Fong, Simon
Tang, Rui
PROCEEDINGS 2016 5TH IIAI INTERNATIONAL CONGRESS ON ADVANCED APPLIED INFORMATICS IIAI-AAI 2016, 2016, : 576 - 582
[32] An adaptive beamforming algorithm for sound source localisation via hybrid compressive sensing reconstruction
Guo, Wenyong
Han, Jianggui
Chen, Hantao
Yu, Li
Wu, Zhe
JOURNAL OF VIBROENGINEERING, 2022, 24 (03) : 591 - 603
[33] An improved self-adaptive bat algorithm
Lyu, Shilei
Huang, Yonglin
Li, Zhen
Xue, Yueju
PROCEEDINGS OF THE 2017 5TH INTERNATIONAL CONFERENCE ON MECHATRONICS, MATERIALS, CHEMISTRY AND COMPUTER ENGINEERING (ICMMCCE 2017), 2017, 141 : 1556 - 1560
[34] Adaptive recovery algorithm for compressive sensing based on Fourier basis
Lü, Fangxu
Zhang, Jincheng
Wang, Quan
Wang, Yu
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 2014, 40 (04): : 544 - 550
[35] QPSK Signal Reconstruction using Compressive Sensing Algorithms
Malleswari, P. Naga
Bindu, Ch Hima
Prasad, K. Satya
PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON BIG DATA ANALYTICS AND COMPUTATIONAL INTELLIGENCE (ICBDAC), 2017, : 298 - 302
[36] Nonlinear regression A*OMP for compressive sensing signal reconstruction
Liu, Tao
Qiu, Tianshuang
Dai, Ruijiao
Li, Jingchun
Chang, Liang
Li, Rong
DIGITAL SIGNAL PROCESSING, 2017, 69 : 11 - 21
[37] Adaptive Filter-based Reconstruction Engine Design for Compressive Sensing
Huang, Nai-Shan
Lin, Yu-Min
Chen, Yi
Wu, An-Yeu
2014 IEEE ASIA PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS (APCCAS), 2014, : 499 - 502
[38] Adaptive Sparsity Reconstruction Method for Ultrasonic Images Based on Compressive Sensing
Zeng, Chun-yan
Ma, Li-hong
Du, Ming-hui
Tian, Jing
2012 12TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS & VISION (ICARCV), 2012, : 1364 - 1368
[39] A Self-Adaptive Algorithm for the Common Solution of the Split Minimization Problem and the Fixed Point Problem
Kaewyong, Nattakarn
Sitthithakerngkiet, Kanokwan
AXIOMS, 2021, 10 (02)
[40] A Sparsity Adaptive Signal Reconstruction Algorithm
Li, Zhou
Cui, Chen
Yi, Renjie
2017 2ND INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC 2017), 2017, : 852 - 857

← 1 2 3 4 5 →