Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Progressive Compressed Sensing and Reconstruction of Multidimensional
  Signals Using Hybrid Transform/Prediction Sparsity Model   Compressed sensing (CS) is an innovative technique allowing to represent
signals through a small number of their linear projections. Hence, CS can be
thought of as a natural candidate for acquisition of multidimensional signals,
as the amount of data acquired and processed by conventional sensors could
create problems in terms of computational complexity. In this paper, we propose
a framework for the acquisition and reconstruction of multidimensional
correlated signals. The approach is general and can be applied to D dimensional
signals, even if the algorithms we propose to practically implement such
architectures apply to 2-D and 3-D signals. The proposed architectures employ
iterative local signal reconstruction based on a hybrid transform/prediction
correlation model, coupled with a proper initialization strategy.

5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
12
The categories of this paper are: nucl-th
30
The categories of this paper are: q-alg