arXiv · 2201.12244
Data Assimilation using Time-Delay Nudging in the Presence of Gaussian Noise
Abstract
We study a discrete-in-time data-assimilation algorithm based on nudging through a time-delayed feedback control in which the observational measurements have been contaminated by a Gaussian noise process. In the context of the two-dimensional incompressible Navier-Stokes equations we prove the expected value of the square-error between the approximating solution and the reference solution over time is proportional to the variance of the noise up to a logarithmic correction. The qualitative behavior and physical relevance of our analysis is further illustrated by numerical simulation.
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Emine Celik, Eric Olson. 2022-01-28. Data Assimilation using Time-Delay Nudging in the Presence of Gaussian Noise. https://arxiv.org/abs/2201.12244
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