Title
Deterministic Construction of Compressed Sensing Matrices using BCH Codes
Abstract
In this paper we introduce deterministic $m\times n$ RIP fulfilling $\pm 1$ matrices of order $k$ such that $\frac{\log m}{\log k}\approx \frac{\log(\log_2 n)}{\log(\log_2 k)}$. The columns of these matrices are binary BCH code vectors that their zeros are replaced with -1 (excluding the normalization factor). The samples obtained by these matrices can be easily converted to the original sparse signal; more precisely, for the noiseless samples, the simple Matching Pursuit technique, even with less than the common computational complexity, exactly reconstructs the sparse signal. In addition, using Devore's binary matrices, we expand the binary scheme to matrices with $\{0,1,-1\}$ elements.
Year
Venue
Keywords
2009
Clinical Orthopaedics and Related Research
deterministic matrices,bch codes.,index terms—compressed sensing,restricted isometry property,bch code,indexing terms,computational complexity,matching pursuit,compressed sensing
Field
DocType
Volume
Matching pursuit,Discrete mathematics,Combinatorics,Normalization (statistics),Approx,Matrix (mathematics),BCH code,Mathematics,Compressed sensing,Binary number,Computational complexity theory
Journal
abs/0908.0
Citations 
PageRank 
References 
0
0.34
9
Authors
2
Name
Order
Citations
PageRank
Arash Amini117822.46
Farrokh Marvasti211313.55