منابع مشابه
Biased Cramér-Rao lower bound calculations for inequality-constrained estimators.
Unbiased Cramér-Rao lower bound (CRB) theory can be used to calculate lower bounds to the variances of unbiased estimates of a set of parameters given only the probability density function of a random vector conditioned on the true parameter values. However, when the estimated parameter values are required to satisfy inequality constraints such as positivity, the resulting estimator is typicall...
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summary While all nonsequential unbiased estimators of the normal mean have variances which must obey the Cramer-Rao inequality, it is shown that some sequential unbiased estimators do not.
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Cramér-Rao lower bounds (CRLBs) are proposed for deterministic parameter estimation under model mismatch conditions where the assumed data model used in the design of the estimators differs from the true data model. The proposed CRLBs are defined for the family of estimators that may have a specified bias (gradient) with respect to the assumed model. The resulting CRLBs are calculated for a lin...
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This work deals with the Sequential Cramér-Rao Lower Bound (SCRLB) for sequential target state estimators for a bistatic tracking problem. In the context of tracking, the SCRLB provides a powerful tool, enabling one to determine a lower bound on the optimal achievable accuracy of target state estimation. The bistatic SCRLBs are analyzed and compared to the monostatic counterparts for a fixed ta...
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We consider the problem of autonomously locating a number of asynchronous sensor nodes in a wireless network. A strong focus lies on reducing the processing resources needed to solve the relative positioning problem, an issue of great interest in resourceconstrained wireless sensor networks. In the first part of the paper, based on a well-known derivation of the Cramér-Rao lower bound for the a...
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ژورنال
عنوان ژورنال: Journal of Statistical Planning and Inference
سال: 1980
ISSN: 0378-3758
DOI: 10.1016/0378-3758(80)90034-8