Sparse signal reconstruction via generalized two-stage thresholding  

作　　者：Heping SONG Zehong AI Yuping LAI Hongying MENG Qirong MAO 

机构地区：[1]School of Computer Science and Telecommunications Engineering,Jiangsu University,Zhenjiang 212012,China [2]Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace,Jiangsu University,Zhenjiang 212012,China [3]School of Cyberspace Security,Beijing University of Posts and Telecommunications,Beijing 100875,China [4]Department of Electronic Computer Engineering,Brunel University London,Middlesex UB83PH,UK

出　　处：《Science China(Information Sciences)》2022年第3期284-285,共2页中国科学（信息科学）（英文版）

基　　金：supported by Beijing Municipal Natural Science Foundation(Grant No.4194076);National Natural Science Foundation of China(Grant Nos.U1836220,61672267);Jiangsu Province Natural Science Foundation(Grant No.BK20170558);China Scholarship Council(Grant No.202008320094)。

摘　　要：Dear editor,The sparse representation model has received a great amount of attention in various signal and image processing applications.Compressed sensing(CS)[1]has consistently focused on devising sparse representation methods that seek to efficiently reconstruct a k-sparse(only k nonzero entries,k<<n)underlying n-length signal via a much smaller number of compressed measurements of length-m(m<<n).

关 键 词：REPRESENTATION nonzero ENTRIES 

分 类 号：TN911.7[电子电信—通信与信息系统]