Binary generalized orthogonal matching pursuit

被引：0
|
作者：
Haifeng Li
Hao Ying
Xiaoli Liu
机构：
[1] Henan Normal University,Henan Engineering Laboratory for Big Data Statistical Analysis and Optimal Control, College of Mathematics and Information Science
[2] Jinan University,College of Information Science and Technology
来源：
Japan Journal of Industrial and Applied Mathematics | 2024年 / 41卷
关键词：
Sparse recovery; Binary sparse signal; Restricted isometry property; Mutual coherence; Compressed sensing; 94A12; 65F22; 65J22;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In signal processing, it is usually to meet the recovery of K-sparse binary signal. In order to reconstruct the K-sparse binary signal, the binary generalized orthogonal matching pursuit (BgOMP) algorithm is proposed in this paper. By using mutual coherence and restricted isometry property (RIP), the theoretical performance of the BgOMP algorithm is also investigated. Based on the results of simulation tests, BgOMP is better than the binary MP (BMP) algorithm.
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页码：1 / 12
页数：11
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