On the Performance of Compressed Sensing with Partially Correct Support

Authors:
Wenbo Xu;Jiaru Lin;Kai Niu;Zhiqiang He
Affiliations:
Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China 100876;Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China 100876;Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China 100876;Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China 100876
Venue:
Wireless Personal Communications: An International Journal
Year:
2013

Citing 6
Cited 0

Modified-CS: modifying compressive sensing for problems with partially known support

ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
Fast communication: A short note on compressed sensing with partially known signal support

Signal Processing
LS-CS-residual (LS-CS): compressive sensing on least squares residual

IEEE Transactions on Signal Processing
Large system performance of linear multiuser receivers in multipath fading channels

IEEE Transactions on Information Theory
On the capacity of spatially correlated MIMO Rayleigh-fading channels

IEEE Transactions on Information Theory
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit

IEEE Transactions on Information Theory

Quantified Score

Hi-index	0.00

Visualization

Abstract

In compressed sensing, many practical recovery algorithms perform linear reconstruction of the nonzero entries of the sparse signal after deriving the underlying support. When this support is partially correct, we develop the mean square error of the reconstructed signals. The exactness of the analytical results is verified by simulations.