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13 - Blending Inverse Problems and Data Assimilation

Published online by Cambridge University Press:  27 July 2023

Daniel Sanz-Alonso
Affiliation:
University of Chicago
Andrew Stuart
Affiliation:
California Institute of Technology
Armeen Taeb
Affiliation:
University of Washington
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Summary

This chapter brings together the material in the first two parts of these notes, demonstrating how the principles and ideas underpinning the derivation of extended and ensemble Kalman filters for data assimilation can be used to design ensemble Kalman methods for inverse problems.

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Publisher: Cambridge University Press
Print publication year: 2023

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