Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Blind Calibration in Compressed Sensing using Message Passing Algorithms   Compressed sensing (CS) is a concept that allows to acquire compressible
signals with a small number of measurements. As such it is very attractive for
hardware implementations. Therefore, correct calibration of the hardware is a
central is- sue. In this paper we study the so-called blind calibration, i.e.
when the training signals that are available to perform the calibration are
sparse but unknown. We extend the approximate message passing (AMP) algorithm
used in CS to the case of blind calibration. In the calibration-AMP, both the
gains on the sensors and the elements of the signals are treated as unknowns.
Our algorithm is also applica- ble to settings in which the sensors distort the
measurements in other ways than multiplication by a gain, unlike previously
suggested blind calibration algorithms based on convex relaxations. We study
numerically the phase diagram of the blind calibration problem, and show that
even in cases where convex relaxation is pos- sible, our algorithm requires a
smaller number of measurements and/or signals in order to perform well.

30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga