计算机应用研究2018，Vol.35Issue(4)：1084-1087,4.DOI:10.3969/j.issn.1001-3695.2018.04.027
基于变步长的正则回溯SAMP压缩感知重构算法
SAMP-RB compressed sensing reconstruction algorithm based on variable step
摘要
Abstract
SAMP based on regularized backtracking is an efficient algorithm for compressed sensing reconstruction algorithm,it introduced backtracking idea in the atomic selection stage,improved the precision of reconstruction,reduced the time of reconstruction.But in the reconstruction process of SAMP-RB algorithm,the idea of the step size was invariables,and it was easy to cause over-estimation or under-estimation because of the unreasonable step length.Aiming at this problem,this paper proposed a method of selecting the step size of the parabolic function and introduced it into the SAMP-RB algorithm to improve the approximation speed when the residuals were large and the approximation accuracy when the residuals were small.The results of theoretical analysis and simulation show that the improved SAMP-PVRB algorithm reduces the reconstruction time by about 20％ while improving the reconstruction precision.The validity of the improved algorithm is verified.关键词
压缩感知/正则回溯/变步长/重构精度Key words
compressed sensing/regularized backtracking/variable step/reconstruction precision分类
信息技术与安全科学引用本文复制引用
杜秀丽,胡兴,顾斌斌,陈波,邱少明..基于变步长的正则回溯SAMP压缩感知重构算法[J].计算机应用研究,2018,35(4):1084-1087,4.基金项目
辽宁省教育厅项目(L201449S) （L201449S）
