DocumentCode
3773584
Title
Modified Reduced Look Ahead Orthogonal Matching Pursuit under the Condition of Unknown Sparsity
Author
Guan Chenhe
Author_Institution
Sch. of Electron. Inf. &
Volume
2
fYear
2015
Firstpage
79
Lastpage
82
Abstract
This paper introduces the basic information about compressive sensing theory and some reconstruction algorithms, such as Orthogonal Matching Pursuit (OMP) and Reduced Look Ahead Orthogonal Matching Pursuit (RLAOMP). RLAOMP performs well in reconstruction, but it needs the exact sparsity. We introduces a modified sparsity adaptive version of RLAOMP, which uses a Modified Sparsity Adaptive Matching Pursuit instead of the Subspace Pursuit to estimate the sparsity. The simulation results showed that it performs well under the condition of unknown sparsity.
Keywords
"Matching pursuit algorithms","Sensors","Estimation","Reconstruction algorithms","Compressed sensing","Sparse matrices","Atomic measurements"
Publisher
ieee
Conference_Titel
Computational Intelligence and Design (ISCID), 2015 8th International Symposium on
Print_ISBN
978-1-4673-9586-1
Type
conf
DOI
10.1109/ISCID.2015.161
Filename
7469085
Link To Document