Achievable MSE lower bounds in non-bayesian biased estimation

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2 Scopus citations

Abstract

In this paper, a new structured approach for obtaining uniformly best biased (UBB) estimators, in the mean-square-error (MSE) sense, is established. We show that if a UBB estimator exists, then it is uniquely given by the locally best biased (LBB) estimator. A necessary and sufficient condition for the existence of a UBB estimator is derived, and it is shown that if there exists an optimal bias, such that this condition is satisfied, then it is unique, and the UBB estimator is directly obtained from the LBB estimator. The UBB estimator is derived in a non-linear Gaussian estimation problem. In comparison to the maximum-likelihood estimator, we show that the UBB estimator exhibits superior estimation performance in the MSE sense.

Original languageEnglish
Title of host publication2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010
Pages117-120
Number of pages4
DOIs
StatePublished - 20 Dec 2010
Event2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010 - Jerusalem, Israel
Duration: 4 Oct 20107 Oct 2010

Publication series

Name2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010

Conference

Conference2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010
Country/TerritoryIsrael
CityJerusalem
Period4/10/107/10/10

Keywords

  • Locally best biased estimators
  • MMSE estimation
  • Non-Bayesian estimation
  • Parameter estimation
  • Uniformly best biased estimators

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