Study on Dynamic Compressed Sensing Based on the Homotopy Algorithm to process streaming signals

yang jin; Lizhi

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Study on Dynamic Compressed Sensing Based on the Homotopy Algorithm to process streaming signals

更新时间：2023-11-14

- Study on Dynamic Compressed Sensing Based on the Homotopy Algorithm to process streaming signals
- Advanced Engineering Sciences Vol. 47, Issue Z1, Pages: 136-141(2015)
- 作者机构：
  
  四川大学
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2015，
  
  Published Online：18 December 2014，
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杨谨,李智.基于同伦算法的时变流信号动态压缩感知研究[J].工程科学与技术,2015,47(Z1):136-141.

yang jin, Lizhi. Study on Dynamic Compressed Sensing Based on the Homotopy Algorithm to process streaming signals. [J]. Advanced Engineering Sciences 47(Z1):136-141(2015)
杨谨,李智.基于同伦算法的时变流信号动态压缩感知研究[J].工程科学与技术,2015,47(Z1):136-141. DOI：

yang jin, Lizhi. Study on Dynamic Compressed Sensing Based on the Homotopy Algorithm to process streaming signals. [J]. Advanced Engineering Sciences 47(Z1):136-141(2015) DOI：

摘要

中文摘要: 为了解决传统压缩感知在处理时变流信号时易引发的效率低下、块效应、延迟高等问题，本文提出了基于L1同伦恢复算法的时变同伦算法，且以医学领域的时变心电信号为例充分证明了该算法的实践可行性。该算法通过对重叠的信号时间采集窗口的滑动控制，压缩采样当下窗口中的待测数据并用L1同伦恢复算法实时恢复出原信号。仿真表明，该算法能够快速实时地压缩采样并精确重构时变的心电信号，其重构信号的相对误差控制在10-2范围内，能有效地解决存储庞大的动态心电图数据的难题。

Abstract

Abstract:Currently most of the compressed sensing to date has focused on static finite-dimension signals. The real-time homotopy algorithm based on the L1-homotopy recovery algorithm was proposed in this paper when dividing signal into disjoint blocks and processing each block independently is either infeasible or inefficient for time-varying streaming signals. The method iteratively processed measurements over a sliding overlapping window and chosed the L1-homotopy recovery algorithm that could avoid solving a new L1 program from scratch at the next iteration to solve a weighted L1-norm problem for estimating sparse coefficients. The algorithm had also been fully proved that it could be used to process electrocardiosignals in the field of medicine. Our experiment results on very long real-time electrocardiosignals demonstrated the good performance of the algorithm in real-time system

with the relative error of the reconstructed signal controlled within 10-2

which effectively lessened great storage burden the ambulatory electrocardiograph (ECG) had brought about.

关键词

压缩感知块效应L1同伦恢复算法心电图

Keywords

Compressed sensingBlocking artifactL1-homotopy recovery algorithmECG

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