Nonlinear modal analysis via non-parametric machine learning tools

Dervilis, N. orcid.org/0000-0002-5712-7323, Simpson, T.E., Wagg, D. et al. (1 more author) (2018) Nonlinear modal analysis via non-parametric machine learning tools. Strain. ISSN 0039-2103

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 John Wiley & Sons, Ltd. This is an author produced version of a paper subsequently published in Strain. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Manifold learning; modal decomposition; nonlinear dynamical systems; pattern recognition
Dates:
  • Accepted: 28 August 2018
  • Published (online): 15 October 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Funding Information:
FunderGrant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/K003836/2
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/K003836/1
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/J016942/1
Depositing User: Symplectic Sheffield
Date Deposited: 13 Sep 2018 11:15
Last Modified: 17 Oct 2018 08:30
Published Version: https://doi.org/10.1111/str.12297
Status: Published online
Publisher: Wiley
Refereed: Yes
Identification Number: https://doi.org/10.1111/str.12297

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