摘要
为了减少无线传感器网络(WSNs)心电信号的压缩感知重构时间,提出一种面向心电(ECG)信号的二分法稀疏度自适应匹配追踪重构算法。基于二分法快速接近真实稀疏度的值,并通过相邻迭代之间残差范数值差的绝对值确定下一轮迭代计算区间。实验结果表明:与传统稀疏自适应匹配追踪重构算法相比较,改进算法可显著降低重构时间并接近子空间追踪算法和正交匹配追踪算法;与子空间追踪算法和正交匹配追踪算法相比,峰值信噪比平均提升了6.29%和5.43%。
To reduce the time consumption in the reconstruction of electrocardiograph(ECG)signals for the wireless sensor networks(WSNs),a dichotomy sparsity adaptive matching pursuit(DSAMP)algorithm for compressed sensing without knowing sparsity is proposed.The algorithm calculates the stage value for approaching the real sparsity based on dichotomy,and determines the direction of stage switching by the absolute value of the difference in residual norm between two adjacent iterations.Results show that the runtime of DSAMP can be reduced compared with that of sparsity adaptive matching pursuit and is similar to those of subspace pursuit and orthogonal matching pursuit.The peak signal to noise ratio of the DSAMP is improved 6.29%and 5.43%,compared with the that of orthogonal matching pursuit and subspace pursuit on average,respectively.
作者
王涛
田青
虞致国
孙益洲
顾晓峰
WANG Tao;TIAN Qing;YU Zhiguo;SUN Yizhou;GU Xiaofeng(Engineering Research Center of Internet of Things Technology Applications,Ministry of Education,Department of Electronic Engineering,Jiangnan University,Wuxi 214122,China;Taihu University of Wuxi,Wuxi 214064,China)
出处
《传感器与微系统》
CSCD
北大核心
2021年第4期131-134,138,共5页
Transducer and Microsystem Technologies
基金
中央高校基本科研业务费专项资金资助项目(JUSRP51510)
江苏省研究生科研与实践创新计划项目(SJCX18-0647)
江苏省物联网应用技术重点建设实验室资助项目。
关键词
压缩感知
心电(ECG)
重构
自适应匹配追踪
compressed sensing
electrocardiograph(ECG)
reconstruction
adaptive matching pursuit
