Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Graded Quantization: Democracy for Multiple Descriptions in Compressed
  Sensing   The compressed sensing paradigm allows to efficiently represent sparse
signals by means of their linear measurements. However, the problem of
transmitting these measurements to a receiver over a channel potentially prone
to packet losses has received little attention so far. In this paper, we
propose novel methods to generate multiple descriptions from compressed sensing
measurements to increase the robustness over unreliable channels. In
particular, we exploit the democracy property of compressive measurements to
generate descriptions in a simple manner by partitioning the measurement vector
and properly allocating bit-rate, outperforming classical methods like the
multiple description scalar quantizer. In addition, we propose a modified
version of the Basis Pursuit Denoising recovery procedure that is specifically
tailored to the proposed methods. Experimental results show significant
performance gains with respect to existing methods.

37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg