Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A New Perspective and Extension of the Gaussian Filter   The Gaussian Filter (GF) is one of the most widely used filtering algorithms;
instances are the Extended Kalman Filter, the Unscented Kalman Filter and the
Divided Difference Filter. GFs represent the belief of the current state by a
Gaussian with the mean being an affine function of the measurement. We show
that this representation can be too restrictive to accurately capture the
dependences in systems with nonlinear observation models, and we investigate
how the GF can be generalized to alleviate this problem. To this end, we view
the GF from a variational-inference perspective. We analyse how restrictions on
the form of the belief can be relaxed while maintaining simplicity and
efficiency. This analysis provides a basis for generalizations of the GF. We
propose one such generalization which coincides with a GF using a virtual
measurement, obtained by applying a nonlinear function to the actual
measurement. Numerical experiments show that the proposed Feature Gaussian
Filter (FGF) can have a substantial performance advantage over the standard GF
for systems with nonlinear observation models.

16
The categories of this paper are: stat
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph