基于自适应加速前向后向匹配追踪的压缩感知重构算法

潘作舟; 孟宗; 李晶; 石颖

doi:10.11959/j.issn.1000-436x.2020006

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基于自适应加速前向后向匹配追踪的压缩感知重构算法

学术论文 | 更新时间：2024-06-05

- 基于自适应加速前向后向匹配追踪的压缩感知重构算法
- Compressed sensing reconstruction algorithm based on adaptive acceleration forward-backward pursuit
- 通信学报 2020年41卷第1期页码：25-32
- 作者机构：
  
  燕山大学电气工程学院，河北秦皇岛 066004
- 作者简介：
  
  [ "潘作舟（1994- ），男，安徽巢湖人，燕山大学博士生，主要研究方向为多传感器信号融合与增强、压缩感知重构算法、转子轴承寿命预测等" ]
  [ "孟宗（1977- ），男，河北保定人，博士，燕山大学教授、博士生导师，主要研究方向为信号分析与处理、旋转机械故障诊断等" ]
  [ "李晶（1990- ），女，河北承德人，燕山大学博士生，主要研究方向为压缩感知稀疏表示方法" ]
  [ "石颖（1995- ），女，河北承德人，燕山大学硕士生，主要研究方向为压缩感知重构算法" ]
- 基金信息：
  
  国家自然科学基金资助项目(51575472);河北省自然科学基金资助项目(E2019203448);河北省创新基金资助项目(CXZZBS2020047)
- DOI：10.11959/j.issn.1000-436x.2020006
  中图分类号： TN911.7
- 网络出版日期：2020-01，
  
  纸质出版日期：2020-01-25
- 稿件说明：
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潘作舟, 孟宗, 李晶, 等. 基于自适应加速前向后向匹配追踪的压缩感知重构算法[J]. 通信学报, 2020,41(1):25-32.

Zuozhou PAN, Zong MENG, Jing LI, et al. Compressed sensing reconstruction algorithm based on adaptive acceleration forward-backward pursuit[J]. Journal on communications, 2020, 41(1): 25-32.
潘作舟, 孟宗, 李晶, 等. 基于自适应加速前向后向匹配追踪的压缩感知重构算法[J]. 通信学报, 2020,41(1):25-32. DOI： 10.11959/j.issn.1000-436x.2020006.

Zuozhou PAN, Zong MENG, Jing LI, et al. Compressed sensing reconstruction algorithm based on adaptive acceleration forward-backward pursuit[J]. Journal on communications, 2020, 41(1): 25-32. DOI： 10.11959/j.issn.1000-436x.2020006.

摘要

针对传统前向后向匹配追踪（FBP）算法运行时间较长的问题，提出了一种自适应加速前向后向匹配追踪（AAFBP）算法。AAFBP算法的重构过程可分为2个阶段，在前向阶段利用自适应阈值来选取适量原子加入支撑集，在后向回溯过程中以原子的投影系数大小作为删除依据，利用自适应删除阈值来进行原子的删除，同时克服了自适应过程中存在的回溯过度现象。所提方法能够保证选入原子数量更具随机性，使每次迭代保留更多的正确原子。一维稀疏信号和二维图像的仿真结果表明，AAFBP算法在重构精度和运算时间上都更具有优势。

Abstract

Aiming at the long running time problem of the traditional forward-backward pursuit (FBP) algorithm

an adaptive acceleration forward-backward pursuit (AAFBP) algorithm was proposed.The reconstruction process of AAFBP algorithm can be divided into two stages.In the forward stage

the AAFBP algorithm used the adaptive threshold to select the right amount of atoms to join the support set.In the backward stage

based on the projection coefficient of the atoms

the deletion threshold was introduced to remove the atoms adaptively and the excessive backtracking phenomenon in adaptive process was overcome simultaneously.The proposed method can ensure the number of the selected atoms more random

and more right atoms were retained in each iteration.The simulation results of one-dimensional sparse signal and two-dimensional image show that the AAFBP algorithm has more advantages in both the accuracy of reconstruction and the running time.

关键词

Keywords

references

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