Nonlinear system identification in structural dynamics: A short (and biased) history

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dc.contributor.author Worden, K en
dc.contributor.author Kerschen, G en
dc.contributor.author Vakakis, AF en
dc.contributor.author Golinval, JC en
dc.date.accessioned 2014-03-01T02:51:08Z
dc.date.available 2014-03-01T02:51:08Z
dc.date.issued 2007 en
dc.identifier.issn 21915644 en
dc.identifier.uri http://hdl.handle.net/123456789/35391
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-84861548219&partnerID=40&md5=99f727283c11b4a3497e3011da60a53a en
dc.subject.other Input/output datum en
dc.subject.other Mathematical theory en
dc.subject.other Linear systems en
dc.subject.other Nonlinear dynamical systems en
dc.subject.other Structural dynamics en
dc.title Nonlinear system identification in structural dynamics: A short (and biased) history en
heal.type conferenceItem en
heal.publicationDate 2007 en
heal.abstract Although linear systems are now very well-understood in the context of structural dynamics, this is not at all the case for nonlinear systems. In particular, despite huge advances in the mathematical theory of nonlinear dynamical systems, progress in the difficult field of nonlinear system identification (learning of models from measured input/output data) has largely remained fairly slow and incremental. This is not to say that there have been no major successes in the field in its comparatively short history, and the objective of this paper is to present some of the highlights, as perceived by the authors, and to pave the way for a second paper discussing new developments and possibilities for the future. en
heal.journalName Conference Proceedings of the Society for Experimental Mechanics Series en

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