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2015-04-20

Kouritzin, Michael A.

A large class of discrete-time branching particle filters with Bayesian model selection ca-pabilities and effective resampling is introduced in algorithmic form, shown empirically to outperform the popular bootstrap algorithm and analyzed mathematically. The particles interact weakly in the...

1997

Kouritzin, Michael, Dawson, Donald

A general Hilbert-space-based stochastic averaging theory is brought forth herein for arbitrary-order parabolic equations with (possibly long range dependent) random coefficients. We use regularity conditions onView the MathML sourcewhich are slightly stronger than those required to prove...

2015

Kouritzin, Michael A., Newton, Fraser, Wu, Biao

A real-time algorithm to produce correlated random fields on general undirected graphs has been used in CAPTCHA generation and optical character recognition. This algorithm can not simulate all possible joint graph distributions but does match all marginal vertex distributions as well as...

2008

Kouritzin, Michael, Long, H.

In this paper, we give a direct derivation of the Duncan–Mortensen–Zakai filtering equation, without assuming right continuity of the signal, nor its filtration, and without the usual finite energy condition. As a consequence, the Fujisaki–Kallianpur–Kunita equation is also derived. Our results...

1997

Kouritzin, Michael

Herein, an averaging theory for the solutions to Cauchy initial value problems of arbitrary order,ε-dependent parabolic partial differential equations is developed. Indeed, by directly developing bounds between the derivatives of the fundamental solution to such an equation and derivatives of the...

2014

Kouritzin, Michael, Ren, Y.-X.

Let ℓ be Lebesgue measure and X=(Xt,t≥0;Pμ) be a supercritical, super-stable process corresponding to the operator −(−Δ)α/2u+βu−ηu2 on Rd with constants β,η>0 and α∈(0,2]. Put View the MathML source, which for each smallθ is an a.s. convergent complex-valued martingale with limit View the MathML...

2008

Kouritzin, Michael, Newton, Fraser, Orsten, Sterling, Wilson, Daniel

Classification of data as true or fabricated has applications in fraud detection and verification of data samples. In this paper, we apply nonlinear filtering to a simplified fraud-detection problem: classifying coin flip sequences as either real or faked. On the way, we propose a method for...

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...

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...

2018-03-27

Yanyu Xiao, Russell Greiner, Mark A. Lewis

In the work, we evaluate the performance of machine learning approaches for predicting successful eradication of aquatic invasive species (AIS) and assess the extent to which eradication of an invasive species depends on the certain specified ecological features of the target ecosystem...