The bayesian abel bound on the mean square error

Alexandre Renaux, Philippe Forster, Pascal Larrabal, Christ Richmond

Research output: Chapter in Book/Report/Conference proceedingChapter


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 publicationBayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
PublisherWiley-IEEE Press
Number of pages4
ISBN (Electronic)9780470544198
ISBN (Print)0470120959, 9780470120958
StatePublished - Jan 1 2007
Externally publishedYes


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

ASJC Scopus subject areas

  • General Computer Science


Dive into the research topics of 'The bayesian abel bound on the mean square error'. Together they form a unique fingerprint.

Cite this