Title :
Sparse Binary Matrices of LDPC Codes for Compressed Sensing
Author :
Lu, Weizhi ; Kpalma, Kidiyo ; Ronsin, Joseph
Author_Institution :
IETR, Univ. Eur. de Bretagne, Rennes, France
Abstract :
We present the sparse binary matrix defined by low-density parity-check (LDPC) codes as measurement matrix in compressed sensing. This kind of matrix owns much stronger orthogonality than current other main measurement matrices. In practice, for a matrix given size, the optimal column degree for high orthogonality can also be determined by progressive edge-growth (PEG) algorithm.
Keywords :
parity check codes; signal reconstruction; sparse matrices; LDPC codes; PEG algorithm; compressed sensing; low-density parity-check codes; optimal column degree; progressive edge-growth algorithm; sparse binary matrices; Compressed sensing; Correlation; Current measurement; Loss measurement; Parity check codes; Signal processing algorithms; Sparse matrices; LDPC codes; compressed sensing; sparse binary matrices;
Conference_Titel :
Data Compression Conference (DCC), 2012
Conference_Location :
Snowbird, UT
Print_ISBN :
978-1-4673-0715-4
DOI :
10.1109/DCC.2012.60
