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Line 32:
|issue=8
|pages=1103–1123
|doi=10.1002/eqe.53|s2cid=110355068
}}</ref> and [[fast Fourier transform]] (FFT)<ref> {{cite journal
|last=Yuen
Line 43 ⟶ 44:
|issue=2
|pages=81–95
|doi=10.1260/136943303769013183|s2cid=62564168
}}</ref> of ambient vibration data. Based on the formulation for FFT data, fast algorithms have been developed for computing the posterior statistics of modal parameters.<ref name="bayomabook" /> Recent developments based on [[EM algorithm]]<ref> {{cite journal
|last=Li
Line 51 ⟶ 53:
|journal=Mechanical Systems and Signal Processing
|year=2019
|volume=132
|pages=490–511
|doi=10.1016/j.ymssp.2019.06.036
|bibcode=2019MSSP..132..490L
|hdl=10356/149983
|s2cid=199124928
|hdl-access=free
}}</ref> show promise for simpler algorithms and reduced coding effort. The fundamental precision limit of OMA has been investigated and presented as a set of '''uncertainty laws''' which can be used for planning ambient vibration tests.<ref name=ulaw2018>
{{cite journal
Line 61 ⟶ 69:
|journal=Mechanical Systems and Signal Processing
|year=2018
|volume=102
|pages=139–157
|doi=10.1016/j.ymssp.2017.09.017
|bibcode=2018MSSP..102..139A
|hdl=10871/30384
|hdl-access=free
Line 75 ⟶ 86:
|journal = Mechanical Systems and Signal Processing
|year=2017
|volume=25
|issue=3
|pages=e2113
|doi=10.1002/stc.2113
|s2cid=55868193
|doi-access=free
}}
</ref> and Section 9.6 of.<ref name="bayomabook" /> For example,
Line 114 ⟶ 130:
|year= 2015
|publisher=John Wiley & Sons
|doi=10.1002/9781118535141
|isbn=9781118535141
|url=https://onlinelibrary.wiley.com/doi/book/10.1002/9781118535141}}
</ref> and Bayesian OMA <ref name=bayomabook>
Line 156 ⟶ 174:
|pages=825–847
|doi=10.1002/stc.424
|s2cid=122257401
|doi-access=free
}}</ref> for Bayesian inference in structural dynamics (relevant for OMA)
| |||