NDLI: Ordering for shift-in-mean of Gauss-Markov random fields with dependent observations

Content Provider	IEEE Xplore Digital Library
Author	Jiangfan Zhang Chuanming Wei Blum, R.S.
Copyright Year	2012
Description	Author affiliation: Electrical and Computer Engineering, Lehigh University, Bethlehem, PA, USA (Jiangfan Zhang; Chuanming Wei; Blum, R.S.)
Abstract	Previous work on ordered transmission approaches showed significant transmission savings but focused entirely on cases with statistically independent observations at a set of sensor nodes. Here we take the first steps toward applying ordering to cases with statistically dependent observations. While we focus on a particular signal detection problem, we choose one of the most well studied problems, detection of a shift-in-mean for a multivariate Gaussian distribution. We employ the well developed theory of decomposable graphical models, and focus on cases where the observations are taken at a set of sensor nodes which can be grouped into a set of cliques. We assume the nodes within a clique are physically close, so that inner-clique communications can be considered extremely inexpensive. We present the computation of the overall likelihood ratio as a new sum, distinctly different from the sum over a set of independent variables, which implies it is possible to employ ordering over the cliques in an attempt to limit the number of communications from each clique to the place where the clique data will be combined. We present results that imply we can often save a significant portion of these transmission, which is lower bounded by half of the number of cliques. We describe necessary conditions for the result to hold and provide numerical results indicating these conditions are satisfied in many cases of practical interest.
Starting Page	65
Ending Page	68
File Size	232407
Page Count	4
File Format	PDF
ISBN	9781467310703
ISSN	2151870X
e-ISBN	9781467310710
DOI	10.1109/SAM.2012.6250563
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Covariance matrix Particle separators Vectors Signal detection Testing Silicon Symmetric matrices
Content Type	Text
Resource Type	Article

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