Cramer-Rao Low Bound Estimation for MSE of SCoSaMP Algorithm

被引：0

作者：

Wang, Cheng ^{[1
]}

Chen, Peng ^{[1
]}

Yang, Huahui ^{[1
]}

Li, Wanling ^{[1
]}

Liu, Deliang ^{[1
]}

Meng, Chen ^{[1
]}

机构：

[1] Shijiazhuang Mech Engn Coll, Shijiazhuang, Hebei, Peoples R China

来源：

COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS | 2019年 / 463卷

基金：

中国国家自然科学基金;

关键词：

SCoSaMP; Compressed sensing; CRLB; MSE;

D O I：

10.1007/978-981-10-6571-2_263

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

SCoSaMP (Signal space-based CoSaMP) is an algorithm with excellent performance proposed for reconstruct signals acquired with Sub-Nyquist sampling system based on redundant Gabor frames. However, there's still no estimation of the lower bound of the error MSE under Gaussian noise and it is hard to estimate the reconstruction performance of SCoSaMP algorithm from a theoretical point of view. This paper presents the CRLB (Cramer-Rao Low Bound) estimation for MSE (Mean Square Estimate) of SCoSaMP algorithm and analyzes the impact factor for noise suppressing, which shows the road for further improving the algorithm.

引用

页码：2158 / 2165

页数：8

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