A variational interpretation of the Cramér–Rao bound

A variational interpretation of the Cramér–Rao bound
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CramérâRao 界的变分解释

DOI:
10.1016/j.sigpro.2020.107917
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发表时间:
2021
期刊:
影响因子:
4.4
通讯作者:
Poor, H. Vincent
Poor, H. Vincent
中科院分区:
工程技术2区
文献类型:
--
作者:
Fauß, Michael;Dytso, Alex;Poor, H. Vincent

文献摘要

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证明了经典界和贝叶斯界都可以通过最小化估计量的均方误差而得到,同时约束底层分布在Fisher信息球内。所提出的结果允许对cram<s:1> - rao界的一些非标准解释,更重要的是,为估计器精度的新界提供了一个模板。
It is shown that both the classic and the Bayesian Cramér–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 Cramér–Rao bound and, more importantly, provide a template for novel bounds on the accuracy of estimators.