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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
Version:
Accepted manuscript

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Publisher copy:
10.1109/ACC.2016.7525183

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Department:
Oxford, MPLS, Engineering Science
Role:
Author
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Department:
Worcester College
Role:
Author
St. John's College, Oxford More from this funder
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Pages:
1820-1825
Publication date:
2016-07-05
Acceptance date:
2016-01-31
DOI:
ISSN:
0743-1619
Pubs id:
pubs:657587
URN:
uri:272e2475-b31d-4f41-8a8b-fad4ac972356
UUID:
uuid:272e2475-b31d-4f41-8a8b-fad4ac972356
Local pid:
pubs:657587
ISBN:
9781467386821

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