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A new approach for estimating the robustness of parameter estimates to measurement noise

Abstract:

We consider the nonlinear, grey-box system identification problem. We establish an approximation of the covariance of a parameter estimate in this context, with several attractive theoretical properties. Our approximation is analogous to the inverse Fisher Information matrix, which approximates the covariance through the Cramer-Rao Lower bound. Indeed, it agrees asymptotically with the Cramer-Rao based covariance estimate in the limit of increasing data, where the theoretical assumptions nece...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ACC.2016.7525183

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Oxford college:
Worcester College
Role:
Author
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Funding agency for:
Papachristodoulou, A
Grant:
EP/M002454/1
St. John's College, Oxford More from this funder
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
Proceedings of the American Control Conference. Journal website
Pages:
1820-1825
Host title:
Proceedings of the American Control Conference
Publication date:
2016-07-01
Acceptance date:
2016-01-31
DOI:
ISSN:
0743-1619
Source identifiers:
657587
ISBN:
9781467386821
Pubs id:
pubs:657587
UUID:
uuid:272e2475-b31d-4f41-8a8b-fad4ac972356
Local pid:
pubs:657587
Deposit date:
2016-11-19

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