电子学报2017，Vol.45Issue(2)：285-290,6.DOI:10.3969/j.issn.0372-2112.2017.02.004
一种基于能量的压缩感知稀疏度估计算法
A Sparsity Order Estimation Algorithm Based on Measured Signal's Energy
摘要
Abstract
Signal sparsity is directly related to the determination of sampling rate and the construction of measurement matrix in compressive sensing.However,the sparsity order is often unknown or time-varying.In this context,investigating blind sparsity order estimation (SOE) techniques is an open research issue.To address this,asymptotic random matrix spectrum analysis theory was used to derive the asymptotic eigenvalue probability distribution function (AEPDF) of the measured signal's covariance matrix.Then,the paper used the relation between the measurement energy and AEPDF to further deduce the corresponding relation between the sparsity order,compressive rate,SNR and the measured signal energy.Subsequently,based on this relation,a technique to estimate the sparsity order using the measured signal energy was proposed.Simulation resuits show that the proposed algorithm can gain higher estimation performance with lower computational complexity compared with the existing algorithm.And the estimation accuracy can be enhanced by increasing the sampling overhead.关键词
压缩感知/稀疏度估计/随机矩阵理论/Stieltjes变换Key words
compressive sensing/sparsity order estimation/random matrix theory/stieltjes transform分类
信息技术与安全科学引用本文复制引用
裴立业,江桦,李明..一种基于能量的压缩感知稀疏度估计算法[J].电子学报,2017,45(2):285-290,6.基金项目
国家自然科学基金(No.61072046) （No.61072046）
