Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian Quickest Detection of Propagating Spatial Events   Rapid detection of spatial events that propagate across a sensor network is
of wide interest in many modern applications. In particular, in communications,
radar, environmental monitoring, and biosurveillance, we may observe
propagating fields or particles. In this paper, we propose Bayesian single and
multiple change-point detection procedures for the rapid detection of
propagating spatial events. It is assumed that the spatial event propagates
across a network of sensors according to the physical properties of the source
causing the event. The multi-sensor system configuration is arbitrary and
sensors may be mobile. We begin by considering a single spatial event and are
interested in detecting this event as quickly as possible, while controlling
the probability of false alarm. Using a dynamic programming framework we derive
the structure of the optimal procedure, which minimizes the average detection
delay (ADD) subject to a false alarm probability upper bound. In the rare event
regime, the optimal procedure converges to a more practical threshold test on
the posterior probability of the change point. A convenient recursive
computation of this posterior probability is derived by using the propagation
pattern of the spatial event. The ADD of the posterior probability threshold
test is analyzed in the asymptotic regime, and specific analysis is conducted
in the setting of detecting attenuating random signals. Then, we show how the
proposed procedure is easy to extend for detecting multiple propagating spatial
events in parallel. A method that provides false discovery rate (FDR) control
is proposed. In the simulation section, it is clearly demonstrated that
exploiting the spatial properties of the event decreases the ADD compared to
procedures that do not utilize this information, even under model mismatch.

6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg