Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Gradient Support Projection Algorithm for Affine Feasibility Problem
  with Sparsity and Nonnegativity   Let $A$ be a real $M \times N$ measurement matrix and $b\in \mathbb{R}^M$ be
an observations vector. The affine feasibility problem with sparsity and
nonnegativity ($AFP_{SN}$ for short) is to find a sparse and nonnegative vector
$x\in \mathbb{R}^N$ with $Ax=b$ if such $x$ exists. In this paper, we focus on
establishment of optimization approach to solving the $AFP_{SN}$. By discussing
tangent cone and normal cone of sparse constraint, we give the first necessary
optimality conditions, $\alpha$-Stability, T-Stability and N-Stability, and the
second necessary and sufficient optimality conditions for the related
minimization problems with the $AFP_{SN}$. By adopting Armijo-type stepsize
rule, we present a framework of gradient support projection algorithm for the
$AFP_{SN}$ and prove its full convergence when matrix $A$ is $s$-regular. By
doing some numerical experiments, we show the excellent performance of the new
algorithm for the $AFP_{SN}$ without and with noise.

10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex