Bayesian system identification of dynamical systems using highly informative training data

Green, P.L., Cross, E.J. and Worden, K. (2014) Bayesian system identification of dynamical systems using highly informative training data. Mechanical Systems and Signal Processing, 56. 109 - 122. ISSN 0888-3270

Abstract

Metadata

Authors/Creators:
  • Green, P.L.
  • Cross, E.J.
  • Worden, K.
Copyright, Publisher and Additional Information: © 2014 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: Bayesian inference; Markov chain Monte Carlo; Nonlinear system identification; Shannon entropy; Tamar bridge
Dates:
  • Published: 4 November 2014
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Funding Information:
FunderGrant number
EPSRCEP/K003836/1
Depositing User: Symplectic Sheffield
Date Deposited: 03 Mar 2015 15:30
Last Modified: 03 Mar 2015 15:30
Published Version: http://dx.doi.org/10.1016/j.ymssp.2014.10.003
Status: Published
Publisher: Elsevier
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.ymssp.2014.10.003

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