Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Distributed Computation of Linear Matrix Equations: An Optimization
  Perspective   This paper investigates the distributed computation of the well-known linear
matrix equation in the form of $AXB = F$, with the matrices A, B, X, and F of
appropriate dimensions, over multi-agent networks from an optimization
perspective. In this paper, we consider the standard distributed
matrix-information structures, where each agent of the considered multi-agent
network has access to one of the sub-block matrices of A, B, and F. To be
specific, we first propose different decomposition methods to reformulate the
matrix equations in standard structures as distributed constrained optimization
problems by introducing substitutional variables; we show that the solutions of
the reformulated distributed optimization problems are equivalent to least
squares solutions to original matrix equations; and we design distributed
continuous-time algorithms for the constrained optimization problems, even by
using augmented matrices and a derivative feedback technique. Moreover, we
prove the exponential convergence of the algorithms to a least squares solution
to the matrix equation for any initial condition.

37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an