Title

Identifying optimal measurement subspace for ensemble Kalman filter

Authors

Authors

N. Zhou; Z. Huang; G. Welch;J. Zhang

Comments

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Abbreviated Journal Title

Electron. Lett.

Keywords

Engineering, Electrical & Electronic

Abstract

To reduce the computational load of the ensemble Kalman filter while maintaining its efficacy, an optimisation algorithm based on the generalised eigenvalue decomposition method is proposed for identifying the most informative measurement subspace. When the number of measurements is large, the proposed algorithm can be used to make an effective trade-off between computational complexity and estimation accuracy.

Journal Title

Electronics Letters

Volume

48

Issue/Number

11

Publication Date

1-1-2012

Document Type

Article

DOI Link

http://dx.doi.org/10.1049/el.2012.0833

Language

English

First Page

618

Last Page

620

WOS Identifier

WOS:000304421900012

ISSN

0013-5194

Recommended Citation

"Identifying optimal measurement subspace for ensemble Kalman filter" (2012). Faculty Bibliography 2010s. 3566.
https://stars.library.ucf.edu/facultybib2010/3566