Parameter estimation for the stochastically perturbed Navier-Stokes equations

Igor Cialenco and Nathan Glatt-Holtz

Stochastic Processes and their Applications, 2011, vol. 121, issue 4, 701-724

Abstract: We consider a parameter estimation problem of determining the viscosity [nu] of a stochastically perturbed 2D Navier-Stokes system. We derive several different classes of estimators based on the first N Fourier modes of a single sample path observed on a finite time interval. We study the consistency and asymptotic normality of these estimators. Our analysis treats strong, pathwise solutions for both the periodic and bounded domain cases in the presence of an additive white (in time) noise.

Keywords: Parameter; estimation; Inverse; problems; Nonlinear; stochastic; partial; differential; equations; Navier-Stokes; equations; Maximum; likelihood; estimators; Stochastic; evolution; equations; Estimation; of; viscosity (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (6)

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