压缩感知OMP算法下信号重建方法研究

数学物理学报 ›› 2021, Vol. 41 ›› Issue (5): 1555-1565.

压缩感知OMP算法下信号重建方法研究

付敏(),郝嘉骏(),解烈军(),王金平*()

^{宁波大学数学与统计学院浙江宁波 315211}

收稿日期:2020-03-09 出版日期:2021-10-26 发布日期:2021-10-08
通讯作者: 王金平 E-mail:2818391447@qq.com;825821801@qq.com;xieliejun@nbu.edu.cn;wangjinping@nbu.edu.cn
作者简介:付敏, E-mail: 2818391447@qq.com|郝嘉骏, E-mail: 825821801@qq.com|解烈军, E-mail: xieliejun@nbu.edu.cn
基金资助:
国家自然科学基金(62071262)

Exact Support Recovery of Sparse Signals from Noisy Measurements

Min Fu(),Jiajun Hao(),Liejun Xie(),Jinping Wang*()

^{School of Mathematics and Statistics, Ningbo University, Zhejiang Ningbo 315211}

Received:2020-03-09 Online:2021-10-26 Published:2021-10-08
Contact: Jinping Wang E-mail:2818391447@qq.com;825821801@qq.com;xieliejun@nbu.edu.cn;wangjinping@nbu.edu.cn
Supported by:
the NSFC(62071262)

摘要/Abstract

摘要：

该文给出了一种OMP算法的改进方法，然后研究在噪声影响下的OMP算法的稀疏重建问题，得到稀疏重建的关于信噪比参数的条件.最后，利用数值模拟验证上述结论.

关键词: 压缩感知OMP算法, 稀疏重建, 信噪比

Abstract:

In this paper, we presents an improved OMP algorithm. Then the sparse reconstruction problem of OMP algorithm under the influence of the noise is studied. The conditions of SNR parameters for sparse reconstruction are obtained. Finnally, numerical simulation is used to verify the above conclusions.

Key words: CS OMP algorithm, Sparse reconstruction, Signal-to-Noise Ratio

中图分类号:

O175.5

付敏,郝嘉骏,解烈军,王金平. 压缩感知OMP算法下信号重建方法研究[J]. 数学物理学报, 2021, 41(5): 1555-1565.

Min Fu,Jiajun Hao,Liejun Xie,Jinping Wang. Exact Support Recovery of Sparse Signals from Noisy Measurements[J]. Acta mathematica scientia,Series A, 2021, 41(5): 1555-1565.

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SNR	支撑的识别
337.85	成功
187.69	成功
112.62	成功
93.85	成功
80.44	成功
3.38	失败