@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",
}