Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Efficient Approximation of the Kalman Filter for Multiple Systems
  Coupled via Low-Dimensional Stochastic Input   We formulate a recursive estimation problem for multiple dynamical systems
coupled through a low dimensional stochastic input, and we propose an efficient
sub-optimal solution. The suggested approach is an approximation of the Kalman
filter that discards the off diagonal entries of the correlation matrix in its
"update" step. The time complexity associated with propagating this approximate
block-diagonal covariance is linear in the number of systems, compared to the
cubic complexity of the full Kalman filter. The stability of the proposed
block-diagonal filter and its behavior for a large number of systems are
analyzed in some simple cases. It is then examined in the context of electric
field estimation in a high-contrast space coronagraph, for which it was
designed. The numerical simulations provide encouraging results for the
cost-efficiency of the newly suggested filter.

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The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
20
The categories of this paper are: acc-phys
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin
33
The categories of this paper are: plasm-ph