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A Dynamic BI–Orthogonal Field Equation Approach to Efficient Bayesian Inversion Cover

A Dynamic BI–Orthogonal Field Equation Approach to Efficient Bayesian Inversion

International Journal of Applied Mathematics and Computer Science
Volume 27 (2017): Issue 2 (June 2017)
By: Piyush M. Tagade and  Han-Lim Choi  
Open Access
|Jul 2017

Authors

Piyush M. Tagade

piyush.tagade@gmail.com

Samsung Advanced Institute of Technology Samsung R&D Institute India,, Bangalore, India

Han-Lim Choi

hanilmc@kaist.ac.kr

Department of Aerospace Engineering KAIST, 291 Daehak-ro, Yuseong,, Deajeon, Korea (Republic of)
DOI: https://doi.org/10.1515/amcs-2017-0016 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
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Language: English
Page range: 229 - 243
Submitted on: Sep 14, 2016
Accepted on: Mar 8, 2017
Published on: Jul 8, 2017
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Bayesian framework,
stochastic partial differential equation,
Karhunen-Loève expansion,
generalized polynomial chaos,
dynamically biorthogonal field equations
Related subjects:
Mathematics,
Applied mathematics

© 2017 Piyush M. Tagade, Han-Lim Choi, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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