Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Recovery of Block-Sparse Representations from Noisy Observations via
  Orthogonal Matching Pursuit   We study the problem of recovering the sparsity pattern of block-sparse
signals from noise-corrupted measurements. A simple, efficient recovery method,
namely, a block-version of the orthogonal matching pursuit (OMP) method, is
considered in this paper and its behavior for recovering the block-sparsity
pattern is analyzed. We provide sufficient conditions under which the
block-version of the OMP can successfully recover the block-sparse
representations in the presence of noise. Our analysis reveals that exploiting
block-sparsity can improve the recovery ability and lead to a guaranteed
recovery for a higher sparsity level. Numerical results are presented to
corroborate our theoretical claim.

22
The categories of this paper are: chao-dyn
5
The categories of this paper are: gr-qc
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg