Communications in Applied Mathematics and Computational Science

Implicit particle filters for data assimilation

Alexandre Chorin, Matthias Morzfeld, and Xuemin Tu

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Abstract

Implicit particle filters for data assimilation update the particles by first choosing probabilities and then looking for particle locations that assume them, guiding the particles one by one to the high probability domain. We provide a detailed description of these filters, with illustrative examples, together with new, more general, methods for solving the algebraic equations and with a new algorithm for parameter identification.

Article information

Source
Commun. Appl. Math. Comput. Sci. Volume 5, Number 2 (2010), 221-240.

Dates
Received: 24 May 2010
Accepted: 19 October 2010
First available in Project Euclid: 20 December 2017

Permanent link to this document
https://projecteuclid.org/euclid.camcos/1513732009

Digital Object Identifier
doi:10.2140/camcos.2010.5.221

Zentralblatt MATH identifier
1229.60047

Subjects
Primary: 60G35: Signal detection and filtering [See also 62M20, 93E10, 93E11, 94Axx] 62M20: Prediction [See also 60G25]; filtering [See also 60G35, 93E10, 93E11]

Keywords
implicit sampling data assimilation particle filter

Citation

Chorin, Alexandre; Morzfeld, Matthias; Tu, Xuemin. Implicit particle filters for data assimilation. Commun. Appl. Math. Comput. Sci. 5 (2010), no. 2, 221--240. doi:10.2140/camcos.2010.5.221. https://projecteuclid.org/euclid.camcos/1513732009


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