典型文献
A NEW SUFFICIENT CONDITION FOR SPARSE RECOVERY WITH MULTIPLE ORTHOGONAL LEAST SQUARES
文献摘要：
A greedy algorithm used for the recovery of sparse signals,multiple orthogonal least squares(MOLS)have recently attracted quite a big of attention.In this paper,we consider the number of iterations required for the MOLS algorithm for recovery of a K-sparse signal x ∈ Rn.We show that MOLS provides stable reconstruction of all K-sparse signals x from y=Ax+w in「6K/M(])iterations when the matrix A satisfies the restricted isometry property(RIP)with isometry constant δ7K≤0.094.Compared with the existing results,our sufficient condition is not related to the sparsity level K.
文献关键词：
中图分类号：
作者姓名：
Haifeng LI;Jing ZHANG
作者机构：
Henan Engineering Laboratory for Big Data Statistical Analysis and Optimal Control,College of Mathematics and Information Science,Henan Normal University,Xinxiang 453007,China
文献出处：
引用格式：
[1]Haifeng LI;Jing ZHANG-.A NEW SUFFICIENT CONDITION FOR SPARSE RECOVERY WITH MULTIPLE ORTHOGONAL LEAST SQUARES)[J].数学物理学报（英文版）,2022(03):941-956
A类：
SUFFICIENT,CONDITION,SPARSE,MULTIPLE,ORTHOGONAL,LEAST,SQUARES,MOLS,Ax+w
B类：
NEW,FOR,RECOVERY,WITH,greedy,algorithm,used,recovery,sparse,signals,multiple,orthogonal,least,squares,have,recently,attracted,quite,big,attention,In,this,paper,we,consider,number,iterations,required,Rn,We,show,that,provides,stable,reconstruction,all,from,6K,when,matrix,satisfies,restricted,isometry,property,RIP,constant,7K,Compared,existing,results,our,sufficient,condition,not,related,sparsity,level
AB值：
0.585148
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