The bayesian abel bound on the mean square error

Alexandre Renaux; Philippe Forster; Pascal Larrabal; Christ Richmond

doi:10.1109/9780470544198.ch12

The bayesian abel bound on the mean square error

Alexandre Renaux
, Philippe Forster
, Pascal Larrabal
, Christ Richmond

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

This paper deals with lower bound on the Mean Square Error (MSE). In the Bayesian framework, we present a new bound which is derived from a constrained optimization problem. This bound is found to be tighter than the Bayesian Bhattacharyya bound, the Reuven-Messer bound, the Bobrovsky-Zakaï bound, and the Bayesian Cramér-Rao bound.

Original language	English (US)
Title of host publication	Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
Publisher	Wiley-IEEE Press
Pages	176-179
Number of pages	4
ISBN (Electronic)	9780470544198
ISBN (Print)	0470120959, 9780470120958
DOIs	https://doi.org/10.1109/9780470544198.ch12
State	Published - Jan 1 2007
Externally published	Yes

Keywords

Bayesian methods
Estimation error
Mean square error methods
Optimization
Parameter estimation
Signal to noise ratio

ASJC Scopus subject areas

General Computer Science

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10.1109/9780470544198.ch12

Cite this

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KW - Estimation error

KW - Mean square error methods

KW - Optimization

KW - Parameter estimation

KW - Signal to noise ratio

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ER -

The bayesian abel bound on the mean square error

Abstract

Keywords

ASJC Scopus subject areas

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