The Bayesian ABEL bound on the mean square ERROR

Alexandre Renaux, Philippe Forster, Pascal Larzabal, Christ Richmond

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

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 languageEnglish (US)
Title of host publication2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
PagesIII9-III12
StatePublished - Dec 1 2006
Externally publishedYes
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: May 14 2006May 19 2006

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
ISSN (Print)1520-6149

Other

Other2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
CountryFrance
CityToulouse
Period5/14/065/19/06

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Renaux, A., Forster, P., Larzabal, P., & Richmond, C. (2006). The Bayesian ABEL bound on the mean square ERROR. In 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings (pp. III9-III12). [1660577] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 3).