Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An alternative approach for distributed parameter estimation under
  Gaussian settings   This paper takes a different approach for the distributed linear parameter
estimation over a multi-agent network. The parameter vector is considered to be
stochastic with a Gaussian distribution. The sensor measurements at each agent
are linear and corrupted with additive white Gaussian noise. Under such
settings, this paper presents a novel distributed estimation algorithm that
fuses the the concepts of consensus and innovations by incorporating the
consensus terms (of neighboring estimates) into the innovation terms. Under the
assumption of distributed parameter observability, introduced in this paper, we
design the optimal gain matrices such that the distributed estimates are
consistent and achieves fast convergence.

28
The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio