On iterative compressed sensing reconstruction of sparse non-negative vectors

Vida Ravanmehr; Ludovic Danjean; David Declercq; Bane Vasić

doi:10.1145/2093698.2093844

On iterative compressed sensing reconstruction of sparse non-negative vectors

Vida Ravanmehr, Ludovic Danjean, David Declercq, Bane Vasić

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We consider the iterative reconstruction of the Compressed Sensing (CS) problem over reals. The iterative reconstruction allows interpretation as a channel-coding problem, and it guarantees perfect reconstruction for properly chosen measurement matrices and sufficiently sparse error vectors. In this paper, we give a summary on reconstruction algorithms for compressed sensing and examine how the iterative reconstruction performs on quasi-cyclic low-density parity check (QC-LDPC) measurement matrices.

Original language	English (US)
Title of host publication	Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11
DOIs	https://doi.org/10.1145/2093698.2093844
State	Published - 2011
Event	4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11 - Barcelona, Spain Duration: Oct 26 2011 → Oct 29 2011

Publication series

Name	ACM International Conference Proceeding Series

Other

Other	4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11
Country/Territory	Spain
City	Barcelona
Period	10/26/11 → 10/29/11

Keywords

bipartite graphs
compressed sensing
low-density parity check codes
message-passing algorithm

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/2093698.2093844

Cite this

On iterative compressed sensing reconstruction of sparse non-negative vectors. / Ravanmehr, Vida; Danjean, Ludovic; Declercq, David et al.
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11. 2011. (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ravanmehr, V, Danjean, L, Declercq, D & Vasić, B 2011, On iterative compressed sensing reconstruction of sparse non-negative vectors. in Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11. ACM International Conference Proceeding Series, 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11, Barcelona, Spain, 10/26/11. https://doi.org/10.1145/2093698.2093844

@inproceedings{8cae3e26a9014b0e8528320eed30cdba,

title = "On iterative compressed sensing reconstruction of sparse non-negative vectors",

abstract = "We consider the iterative reconstruction of the Compressed Sensing (CS) problem over reals. The iterative reconstruction allows interpretation as a channel-coding problem, and it guarantees perfect reconstruction for properly chosen measurement matrices and sufficiently sparse error vectors. In this paper, we give a summary on reconstruction algorithms for compressed sensing and examine how the iterative reconstruction performs on quasi-cyclic low-density parity check (QC-LDPC) measurement matrices.",

keywords = "bipartite graphs, compressed sensing, low-density parity check codes, message-passing algorithm",

author = "Vida Ravanmehr and Ludovic Danjean and David Declercq and Bane Vasi{\'c}",

year = "2011",

doi = "10.1145/2093698.2093844",

language = "English (US)",

isbn = "9781450309134",

series = "ACM International Conference Proceeding Series",

booktitle = "Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11",

note = "4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11 ; Conference date: 26-10-2011 Through 29-10-2011",

}

TY - GEN

T1 - On iterative compressed sensing reconstruction of sparse non-negative vectors

AU - Ravanmehr, Vida

AU - Danjean, Ludovic

AU - Declercq, David

AU - Vasić, Bane

PY - 2011

Y1 - 2011

N2 - We consider the iterative reconstruction of the Compressed Sensing (CS) problem over reals. The iterative reconstruction allows interpretation as a channel-coding problem, and it guarantees perfect reconstruction for properly chosen measurement matrices and sufficiently sparse error vectors. In this paper, we give a summary on reconstruction algorithms for compressed sensing and examine how the iterative reconstruction performs on quasi-cyclic low-density parity check (QC-LDPC) measurement matrices.

AB - We consider the iterative reconstruction of the Compressed Sensing (CS) problem over reals. The iterative reconstruction allows interpretation as a channel-coding problem, and it guarantees perfect reconstruction for properly chosen measurement matrices and sufficiently sparse error vectors. In this paper, we give a summary on reconstruction algorithms for compressed sensing and examine how the iterative reconstruction performs on quasi-cyclic low-density parity check (QC-LDPC) measurement matrices.

KW - bipartite graphs

KW - compressed sensing

KW - low-density parity check codes

KW - message-passing algorithm

UR - http://www.scopus.com/inward/record.url?scp=84856763488&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84856763488&partnerID=8YFLogxK

U2 - 10.1145/2093698.2093844

DO - 10.1145/2093698.2093844

M3 - Conference contribution

SN - 9781450309134

T3 - ACM International Conference Proceeding Series

BT - Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11

T2 - 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11

Y2 - 26 October 2011 through 29 October 2011

ER -

On iterative compressed sensing reconstruction of sparse non-negative vectors

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this