基于变步长的正则化回溯自适应追踪算法

doi:10.3969/j.issn.0372-2112.2018.08.005

电子学报 ›› 2018, Vol. 46 ›› Issue (8): 1829-1834.DOI: 10.3969/j.issn.0372-2112.2018.08.005

基于变步长的正则化回溯自适应追踪算法

王欣¹, 张严心¹, 黄志清²

1. 北京交通大学电子信息工程学院, 北京 100044;
2. 北京工业大学信息学部, 北京 100124

收稿日期:2016-10-18 修回日期:2017-02-02 出版日期:2018-08-25
- 作者简介:
- 王欣女,1991年11月出生,山东聊城人.北京交通大学电子信息工程学院研究生,主要研究方向为无线传感器网络压缩感知.E-mail:18810370162@163.com;张严心 女,1976年2月出生,辽宁盘锦人.北京交通大学电子信息工程学院自动化系先进控制系统研究所副教授,主要研究方向为复杂大系统控制、复杂网络及交通网络控制.E-mail:yxzhang@bjtu.edu.cn;黄志清 男,1970年11月出生,四川自贡人.北京工业大学信息学部副教授,主要研究方向为物联网及无线传感器网络.E-mail:zqhuang@bjut.edu.cn
- 基金资助:
- 中央高校基本科研业务费 (No.W16JB00340）; 国家发改委项目 (No.Q5025001201502）

Regularized Backtracking Adaptive Pursuit Algorithm Based Variable Step-size

WANG Xin¹, ZHANG Yan-xin¹, HUANG Zhi-qing²

1. School of Electronics and Information Engineering, Beijing Jiaotong University of Technology, Beijing 100044, China;
2. Department of Information Science, Beijing University of Technology, Beijing 100124, China

Received:2016-10-18 Revised:2017-02-02 Online:2018-08-25 Published:2018-08-25

摘要/Abstract

摘要： 在压缩感知重构算法中，稀疏度未知及步长大小固定是影响算法精度及运行时间的因素.针对以上不足，本文提出一种基于变步长的正则化回溯自适应追踪算法.该算法首先通过原子匹配测试的方式获得信号的稀疏度估计；将正则化思想和子空间追踪算法的回溯思想相结合，实现原子的二次筛选并筛除不合适的原子；最后，利用变化的步长选择候选集中的原子，帮助完成信号的完整重构.通过仿真实验证明，本文提出的重构算法在重构速度和重构精度上均优于同类算法.

关键词: 压缩感知, 信号重构, 变步长, 自适应追踪

Abstract: In the compressive sensing reconstruction algorithm,the unknown sparsity and the fixed step-size are the factors that affect the reconstruction accuracy and running time of the algorithm.In view of the above shortcomings,we propose a regularized backtracking adaptive pursuit algorithm based variable step-size.Firstly,the sparsity of the signal is obtained by the way of atomic matching test.Then we combine the regularization method with the subspace tracking algorithm to achieve the second screening and remove the atoms which are not appropriate.Finally,we use a variable step-size to select atoms in the candidate set so that we can complete the signal reconstruction.The simulation results show that the proposed algorithm is superior to other algorithms in speed and reconstruction accuracy.

Key words: compressive sensing, signal reconstruction, variable step-size, adaptive pursuit

中图分类号:

TN911.73

王欣, 张严心, 黄志清. 基于变步长的正则化回溯自适应追踪算法[J]. 电子学报, 2018, 46(8): 1829-1834.

WANG Xin, ZHANG Yan-xin, HUANG Zhi-qing. Regularized Backtracking Adaptive Pursuit Algorithm Based Variable Step-size[J]. Acta Electronica Sinica, 2018, 46(8): 1829-1834.

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基于变步长的正则化回溯自适应追踪算法

Regularized Backtracking Adaptive Pursuit Algorithm Based Variable Step-size

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