Assimilation variationnelle de données océanographiques Approches primale et duale
The Back and Forth Nudging algorithm for data assimilation problems : theoretical results on transport equations
In this paper, we consider the back and forth nudging algorithm that has been introduced for data assimilation purposes. It consists of iteratively and alternately solving forward and backward in time the model equation, with a feedback term to the observations. We consider the case of 1-dimensional transport equations, either viscous or inviscid, linear or not (Burgers’ equation). Our aim is to prove some theoretical results on the convergence, and convergence properties, of this algorithm. We...
The Back and Forth Nudging algorithm for data assimilation problems : theoretical results on transport equations
In this paper, we consider the back and forth nudging algorithm that has been introduced for data assimilation purposes. It consists of iteratively and alternately solving forward and backward in time the model equation, with a feedback term to the observations. We consider the case of 1-dimensional transport equations, either viscous or inviscid, linear or not (Burgers’ equation). Our aim is to prove some theoretical results on the convergence,...
A dual data assimilation method for a layered quasi-geostrophic ocean model.
In this paper we introduce the equations of a layered quasi-geostrophic ocean model, and the corresponding data assimilation problem. We first give the variational formulation. We then point out the linear theory of duality. Finally, we apply duality to our nonlinear model by describing an algorithm to solve the data assimilation problem, introducing a dual cost function and a simple way to compute its gradient.
The Back and Forth Nudging algorithm for data assimilation problems : theoretical results on transport equations
In this paper, we consider the back and forth nudging algorithm that has been introduced for data assimilation purposes. It consists of iteratively and alternately solving forward and backward in time the model equation, with a feedback term to the observations. We consider the case of 1-dimensional transport equations, either viscous or inviscid, linear or not (Burgers’ equation). Our aim is to prove some theoretical results on the convergence,...
A topological asymptotic analysis for the regularized grey-level image classification problem
The aim of this article is to propose a new method for the grey-level image classification problem. We first present the classical variational approach without and with a regularization term in order to smooth the contours of the classified image. Then we present the general topological asymptotic analysis, and we finally introduce its application to the grey-level image classification problem.
Variational data assimilation for discrete Burgers equation.
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