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2013-09-10
The equivalences to and the connections between the modulus-of-continuity condition, compact containment and tightness on DE[a, b] with a < b are studied. The results within are tools for establishing tightness for probability measures on DE[a, b] that generalize and simplify prevailing results...
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2013-11-22
We address the missing analog of vague convergence in the weak-converge large-deviations analogy. Specifically, we introduce the weak Laplace principle and show it implies both the well-known weak LDP and the Laplace principle lower bound. Both the weak LDP and weak Laplace principle hold in...
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2013-06-25
Partially-observed microstructure models, containing stochastic volatility, dynamic trading noise and short term inertia, are introduced to address the following questions: (1) Do the observed prices exhibit statistically signicant inertia? (2) Is stochastic volatility (SV) still evident in the...
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2008
Target Obscuration, including foliage or building obscuration of ground targets and landscape or horizon obscuration of airborne targets, plagues many real world filtering problems. In particular, ground moving target identification Doppler radar, mounted on a surveillance aircraft or unattended...
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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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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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2001
Chan, Hubert, Kouritzin, Michael
Filtering is a method of estimating the conditional probability distribution of a signal based upon a noisy, partial, corrupted sequence of observations of the signal. Particle filters are a method of filtering in which the conditional distribution of the signal state is approximated by the...
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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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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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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...