DocumentCode :
700210
Title :
A new Bayesian lower bound on the mean square error of estimators
Author :
Todros, Koby ; Tabrikian, Joseph
Author_Institution :
Dept. of Electr. & Comput. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
fYear :
2008
fDate :
25-29 Aug. 2008
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, the Weiss-Weinstein family of Bayesian lower bounds on the mean-square-error of estimators is extended to an integral form. A new class of Bayesian lower bounds is derived from this integral form by approximating each entry of the vector of estimation error in a closed Hilbert subspace of L2. This Hilbert subspace is spanned by a set of linear transformations of elements in the domain of an integral transform of a particular function, which is orthogonal to any function of the observations. It is shown that new Bayesian bounds can be derived from this class by selecting the particular function from a known set and modifying the kernel of the integral transform. A new computationally manageable lower bound is derived from the proposed class using the kernel of the Fourier transform. The bound is computationally manageable and provides better prediction of the signal-to-noise ratio threshold region, exhibited by the maximum a-posteriori probability estimator. The proposed bound is compared with other known bounds in terms of threshold SNR prediction in the problem of frequency estimation.
Keywords :
Bayes methods; Fourier transforms; Hilbert spaces; frequency estimation; maximum likelihood estimation; mean square error methods; prediction theory; Bayesian lower bound; Fourier transform; Weiss-Weinstein family; closed Hilbert subspace; frequency estimation; integral transform; linear transformation; maximum a posteriori probability estimator; mean square error method; signal-to-noise ratio threshold region prediction; threshold SNR prediction; Abstracts; Hafnium compounds; Joints; Signal to noise ratio; Transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2008 16th European
Conference_Location :
Lausanne
ISSN :
2219-5491
Type :
conf
Filename :
7080742
Link To Document :
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