Book Cover
E-book
Author Sanz-Alonso, Daniel, 1989- author.

Title Inverse problems and data assimilation / Daniel Sanz-Alonso, Andrew Stuart, Armeen Taeb
Published Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2023
©2023

Copies

Description 1 online resource
Series London Mathematical Society student texts ; 107
London Mathematical Society student texts ; 107.
Summary This concise introduction provides an entry point to the world of inverse problems and data assimilation for advanced undergraduates and beginning graduate students in the mathematical sciences. It will also appeal to researchers in science and engineering who are interested in the systematic underpinnings of methodologies widely used in their disciplines. The authors examine inverse problems and data assimilation in turn, before exploring the use of data assimilation methods to solve generic inverse problems by introducing an artificial algorithmic time. Topics covered include maximum a posteriori estimation, (stochastic) gradient descent, variational Bayes, Monte Carlo, importance sampling and Markov chain Monte Carlo for inverse problems; and 3DVAR, 4DVAR, extended and ensemble Kalman filters, and particle filters for data assimilation. The book contains a wealth of examples and exercises, and can be used to accompany courses as well as for self-study
Notes Description based on online resource; title from digital title page (viewed on August 09, 2023)
Subject Inverse problems (Differential equations)
Inverse problems (Differential equations)
Form Electronic book
Author Stuart, Andrew (Professor of mathematics), author
Taeb, Armeen, 1990- author.
ISBN 9781009414319
1009414313