期刊
SIGNAL PROCESSING
卷 182, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.sigpro.2020.107917
关键词
Cramer-Rao bound; Fisher information; Variational techniques
资金
- German Research Foundation (DFG) [424522268]
- U.S. National Science Foundation [CCF-1908308]
Both the classic and Bayesian Cramer-Rao bounds can be obtained by minimizing the mean square error of an estimator while constraining the underlying distribution to be within a Fisher information ball. The results allow for nonstandard interpretations of the Cramer-Rao bound and provide a template for novel bounds on the accuracy of estimators.
It is shown that both the classic and the Bayesian Cramer-Rao bounds can be obtained by minimizing the mean square error of an estimator while constraining the underlying distribution to be within a Fisher information ball. The presented results allow for some nonstandard interpretations of the Cramer-Rao bound and, more importantly, provide a template for novel bounds on the accuracy of estimators. (c) 2020 Elsevier B.V. All rights reserved.
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