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Published June 12, 2017 | Submitted
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Convergence Analysis of the Ensemble Kalman Filter for Inverse Problems: the Noisy Case


We present an analysis of the ensemble Kalman filter for inverse problems based on the continuous time limit of the algorithm. The analysis of the dynamical behaviour of the ensemble allows to establish well-posedness and convergence results for a fixed ensemble size. We will build on the results presented in [Schillings, Stuart 2017] and generalise them to the case of noisy observational data, in particular the influence of the noise on the convergence will be investigated, both theoretically and numerically.

Additional Information

Both authors are grateful to the EPSRC Programme Grant EQUIP for funding of this research. AMS is also grateful to DARPA and to ONR for funding parts of this research.

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Submitted - 1702.07894.pdf


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