The University of Southampton
University of Southampton Institutional Repository

Bayesian inference for uncertain dynamic systems

Bayesian inference for uncertain dynamic systems
Bayesian inference for uncertain dynamic systems
Bayesian inference methods are applied to linear structural dynamic systems with uncertain components. Using an exact low-rank update of the transfer function, the uncertainties may be isolated at the level of the parameters of the system. This allows convenient derivation of the probability of the system response and relatively straightforward application of Bayesian methods. Several such applications are presented analytically and illustrated on benchmark examples.
bayesian inference methods, structural dynamics, transfer function, low-rank update, probability density function
0854329102
13pp
University of Southampton
Lecomte, Christophe
87cdee82-5242-48f9-890d-639a091d0b9c
Forster, J.J.
e3c534ad-fa69-42f5-b67b-11617bc84879
Mace, B.R.
681dd501-6313-441d-86e6-20a90fada824
Ferguson, N.S.
8cb67e30-48e2-491c-9390-d444fa786ac8
Brennan, M.J.
Kovacic, Ivana
Lopes, V.
Murphy, K.
Petersson, B.
Rizzi, S.
Yang, T.
Lecomte, Christophe
87cdee82-5242-48f9-890d-639a091d0b9c
Forster, J.J.
e3c534ad-fa69-42f5-b67b-11617bc84879
Mace, B.R.
681dd501-6313-441d-86e6-20a90fada824
Ferguson, N.S.
8cb67e30-48e2-491c-9390-d444fa786ac8
Brennan, M.J.
Kovacic, Ivana
Lopes, V.
Murphy, K.
Petersson, B.
Rizzi, S.
Yang, T.

Lecomte, Christophe, Forster, J.J., Mace, B.R. and Ferguson, N.S. (2010) Bayesian inference for uncertain dynamic systems. Brennan, M.J., Kovacic, Ivana, Lopes, V., Murphy, K., Petersson, B., Rizzi, S. and Yang, T. (eds.) In Recent Advances Structural Dynamics: Proceedings of the X International Conference. University of Southampton. 13pp .

Record type: Conference or Workshop Item (Paper)

Abstract

Bayesian inference methods are applied to linear structural dynamic systems with uncertain components. Using an exact low-rank update of the transfer function, the uncertainties may be isolated at the level of the parameters of the system. This allows convenient derivation of the probability of the system response and relatively straightforward application of Bayesian methods. Several such applications are presented analytically and illustrated on benchmark examples.

This record has no associated files available for download.

More information

Published date: July 2010
Additional Information: Paper No. 162 (Format - USB Pen Drive)
Keywords: bayesian inference methods, structural dynamics, transfer function, low-rank update, probability density function
Organisations: Statistical Sciences Research Institute, Dynamics Group

Identifiers

Local EPrints ID: 160701
URI: http://eprints.soton.ac.uk/id/eprint/160701
ISBN: 0854329102
PURE UUID: c03e1b69-4f0c-493c-95c7-78c5ce780664
ORCID for J.J. Forster: ORCID iD orcid.org/0000-0002-7867-3411
ORCID for N.S. Ferguson: ORCID iD orcid.org/0000-0001-5955-7477

Catalogue record

Date deposited: 20 Jul 2010 14:44
Last modified: 11 Dec 2021 03:02

Export record

Contributors

Author: Christophe Lecomte
Author: J.J. Forster ORCID iD
Author: B.R. Mace
Author: N.S. Ferguson ORCID iD
Editor: M.J. Brennan
Editor: Ivana Kovacic
Editor: V. Lopes
Editor: K. Murphy
Editor: B. Petersson
Editor: S. Rizzi
Editor: T. Yang

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×