Grain information compressed sensing based on semi-tensor product approach

被引：0

作者：

Jin X.-Y. ^{[1
]}

Xie M.-H. ^{[1
]}

Sun B. ^{[1
]}

机构：

[1] College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou

来源：

| 1600年 / Editorial Board of Jilin University卷 / 51期

关键词：

Compressed sensing; Grain information; Iteratively re-weighted least squares; Semi-tensor product; Signal and information processing;

D O I：

10.13229/j.cnki.jdxbgxb20191098

中图分类号：

学科分类号：

摘要：

In the conventional sampling ways, the cost in data transmission and storage is very high. To reduce the transmission and storage cost of the temperature, a novel compressed sensing system based on semi-tensor product (STP) is proposed. First, a low-dimensional random matrix is generated to globally sample the original data. Then a grouping reconstruction method is proposed to obtain the solution with the iteratively re-weighted least-square (IRLS) algorithm. Numerical results show that the proposed system outperforms conventional way in speed of reconstruction and its comparable quality of reconstruction, which is important for real-time applications. © 2021, Jilin University Press. All right reserved.

引用

页码：379 / 385

页数：6

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