Parameter estimation in the presence of bounded modeling errors

We formulate and solve a new parameter estimation problem in the presence of bounded data uncertainties. The new method is suitable when a priori bounds on the uncertain data are available; its solution guarantees that the effect of the uncertainties will never be unnecessarily overestimated beyond...

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Bibliographic Details
Published in:IEEE signal processing letters 1997-07, Vol.4 (7), p.195-197
Main Authors: Chandrasekaran, S., Golub, G.H., Gu, M., Sayed, A.H.
Format: Article
Language:English
Subjects:
Cost function
Data analysis
Honorary membership
Least squares methods
Measurement errors
Parameter estimation
Robustness
Uncertainty
Upper bound
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Summary:We formulate and solve a new parameter estimation problem in the presence of bounded data uncertainties. The new method is suitable when a priori bounds on the uncertain data are available; its solution guarantees that the effect of the uncertainties will never be unnecessarily overestimated beyond what is reasonably assumed by the a priori bounds.
ISSN:1070-9908
1558-2361
DOI:10.1109/97.596884