Accession Number : ADA609275


Title :   Bayesian Tracking within a Feedback Sensing Environment: Estimating Interacting, Spatially Constrained Complex Dynamical Systems from Multiple Sources of Controllable Devices


Descriptive Note : Final rept. 1 Sep 2010-31 Aug 2012


Corporate Author : WHARTON SCHOOL PHILADELPHIA PA


Personal Author(s) : Fox, Emily B


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a609275.pdf


Report Date : 25 Jul 2014


Pagination or Media Count : 6


Abstract : This grant led to developments in flexible models for complex time series in a range of applications with a focus on Bayesian and Bayesian nonparametric methods. Three fundamental challenges were tackled: (i) capturing evolving correlations in high-dimensional time series with possible missing or irregularly-spaced observations, (ii) performing diverse subset selection over time, and (iii) automatically learning an unknown set of simple underlying temporal structures to describe complex dynamical phenomena. Each of these methods was applied in a range of application domains including neuroimaging, diverse document selection, speaker diarization, stock modeling, and target tracking.


Descriptors :   *STATISTICAL PROCESSES , CLASSIFICATION , MARKOV PROCESSES , TIME SERIES ANALYSIS


Subject Categories : Statistics and Probability
      Cybernetics


Distribution Statement : APPROVED FOR PUBLIC RELEASE