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2002
Kouritzin, Michael, Bauer, Will, Kim, Surrey
Predicting the future state of a random dynamic signal based on corrupted, distorted, and partial observations is vital for proper real-time control of a system that includes time delay. Motivated by problems from Acoustic Positioning Research Inc., we consider the continual automated...
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2002
Kim, Surrey, Kouritzin, Michael, Ballantyne, David
Particle-based nonlinear filters have proven to be effective and versatile methods for computing approximations to difficult filtering problems. We introduce a novel hybrid particle method, thought to possess an excellent compromise between the unadaptive nature of the weighted particle methods...
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2003
Ballantyne, David, Wiersma, Jonathan, Kouritzin, Michael, Hailes, Jarett, Long, Hongwei
A hybrid weighted interacting particle filter, the selectively resampling particle filter (SERP), is used to detect and track multiple ships maneuvering in a region of water. The ship trajectories exhibit nonlinear dynamics and interact in a nonlinear manner such that the ships do not collide....
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2003
Kouritzin, Michael, Ma, Xinjian, Long, Hongwei, Sun, Wei
Nonlinear filtering is an important and effective tool for handling estimation of signals when observations are incomplete, distorted, and corrupted. Quite often in real world applications, the signals to be estimated contain unknown parameters which need to be determined. Herein, we develop and...
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2004
McCrosky, Jesse, Kouritzin, Michael, Blount, Douglas
A hybrid weighted/interacting particle filter, the selectively resampling particle (SERP) filter, is used to detect and track an unknown number of independent targets on a one-dimensional \"racetrack\" domain. The targets evolve in a nonlinear manner. The observations model a sensor positioned...
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2004
Kouritzin, Michael, Long, H., Sun, W.
Herein, we consider direct Markov chain approximations to the Duncan–Mortensen–Zakai equations for nonlinear filtering problems on regular, bounded domains. For clarity of presentation, we restrict our attention to reflecting diffusion signals with symmetrizable generators. Our Markov chains are...
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2004
Zhao, Xingqiu, Long, Hongwei, McCrosky, Jesse, Kim, Surrey, Kouritzin, Michael
In this paper, we discuss multi-target tracking for a submarine model based on incomplete observations. The submarine model is a weakly interacting stochastic dynamic system with several submarines in the underlying region. Observations are obtained at discrete times from a number of sonobuoys...
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2004
Kouritzin, Michael, Kim, Surrey, Sun, Wei, Kim, Hyukjoon
In this note, we consider the problem of detecting network portscans through the use of anomaly detection. First, we introduce some static tests for analyzing traffic rates. Then, we make use of two dynamic chi-square tests to detect anomalous packets. Further, we model network traffic as a...
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2005
Kouritzin, Michael, Kim, H., Hu, Y., Ballantyne, D.
This paper addresses the problem of detecting and tracking an unknown number of submarines in a body of water using a known number of moving sonobuoys. Indeed, we suppose there are N submarines collectively maneuvering as a weakly interacting stochastic dynamical system, where N is a random...
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2005
Herein, we analyze an efficient branching particle method for asymptotic solutions to a class of continuous-discrete filtering problems. Suppose that t→Xt is a Markov process and we wish to calculate the measure-valued process t→μt(⋅)≐P{Xt∈⋅|σ{Ytk, tk≤t}}, where tk=kɛ and Ytk is a distorted,...