华中科技大学学报（自然科学版）2016，Vol.44Issue(8)：62-65,4.DOI:10.13245/j.hust.160813
改进的基于梯度投影的Gram观测矩阵优化算法
Improved optimization algorithm of the Gram measurement matrix based on gradient projection
摘要
Abstract
To solve the optimization problem of measurement matrix in the compressed sensing ,the independence of measurement matrix columns and the coherence between rows of the measurement matrix and columns of sparse basis were analyzed to find out whether they can influence the quality of the reconstruction ,so the QR decomposition was used to enhance the independence of measurement matrix column .By combining the QR decomposition with the Gram measurement matrix based on gra‐dient projection ,an improved algorithm was proposed .The proposed algorithm reduces the correla‐tion between the measurement matrix and sparse matrix by using equiangular tight frame .Secondly , the gradient projection method was used to solve the measurement matrix .Finally ,QR decomposition was used to enhance the independence of measurement matrix column .Simulation results show that the proposed algorithm improves the quality of reconstructed signals compared with the Gram matrix optimization algorithm based on gradient projection .关键词
压缩感知/观测矩阵/QR分解/Gram矩阵/优化算法Key words
compressed sensing/measurement matrix/QR decomposition/Gram matrix/optimization algorithm分类
信息技术与安全科学引用本文复制引用
刘杰平,杨朝煜,方杰,韦岗..改进的基于梯度投影的Gram观测矩阵优化算法[J].华中科技大学学报（自然科学版）,2016,44(8):62-65,4.基金项目
国家自然科学基金资助项目（61327005）；国家工程技术研究中心资助项目（2013FU125X02）；广东省短距离无线探测与通信重点实验室资助项目（2014B030301010）． （）
