Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Practical error estimates for sparse recovery in linear inverse problems   The effectiveness of using model sparsity as a priori information when
solving linear inverse problems is studied. We investigate the reconstruction
quality of such a method in the non-idealized case and compute some typical
recovery errors (depending on the sparsity of the desired solution, the number
of data, the noise level on the data, and various properties of the measurement
matrix); they are compared to known theoretical bounds and illustrated on a
magnetic tomography example.

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The categories of this paper are: hep-ph
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex
1
The categories of this paper are: cs