The Theory of Compressed Sensing and Reconstruction Algorithm

YANG Hai-rong; ZHANG Cheng; DING Da-wei; WEI Sui

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The Theory of Compressed Sensing and Reconstruction Algorithm

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- The Theory of Compressed Sensing and Reconstruction Algorithm
- Acta Electronica Sinica Vol. 39, Issue 1, Pages: 142-148(2011)
- 作者机构：
  
  1. 安徽大学计算智能与信号处理教育部重点实验室,安徽,合肥,230039
  2. 合肥师范学院数学系,安徽,合肥,230061
  3. 安徽大学计算智能与信号处理教育部重点实验室安徽合肥,230039
  4. 合肥师范学院数学系安徽合肥,230061
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.72
- Published：2011
- 稿件说明：
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YANG Hai-rong, ZHANG Cheng, DING Da-wei, et al. The Theory of Compressed Sensing and Reconstruction Algorithm[J]. Acta Electronica Sinica, 2011, 39(1): 142-148.
DOI：

YANG Hai-rong, ZHANG Cheng, DING Da-wei, et al. The Theory of Compressed Sensing and Reconstruction Algorithm[J]. Acta Electronica Sinica, 2011, 39(1): 142-148. DOI：

摘要

压缩传感理论(Compressive Sensing

CS)以远低于Nyquist采样频率的非适应性测量和优化方法高概率重构信号.本文介绍了CS的基本理论、重构算法

包括贪婪、凸优化方法及我们提出的MBOOMP算法;同时

采用0-1组成的随机信号进行性能比较的模拟实验

结果表明我们的算法优于传统的OMP算法.

Abstract

Compressive sensing

by means of the non-adaptive measurements with a well below the Nyquist frequency and optimization methods

reconstruct signal with high probability.In this paper

we introduce the basic theory of compressed sensing and the main reconstruction algorithms

including iterative algorithms as well as our improved MBOOMP algorithm.Meanwhile

the simulation of radom signal which is composed of 0 and 1 are adapted to compare their performance.It is shown that our algorithm is better than typical OMP algorithm.

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