A lower bound on the estimation error for markov processes

Ben Zion Bobrovsky, Moshe Zakai

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

A lower bound on the minimal mean-square error in estimating nonlinear Markov processes is presented. The. bound holds for causal and uncausal flltering. The derivation is based on the Van Trees’ version of the Cramér-Rao inequality.

Original languageEnglish
Title of host publicationBayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
PublisherWiley-IEEE Press
Pages631-634
Number of pages4
ISBN (Electronic)9780470544198
ISBN (Print)0470120959, 9780470120958
DOIs
StatePublished - 1 Jan 2007

Keywords

  • Diffusion processes
  • Estimation error
  • Markov processes
  • Maximum likelihood detection
  • Nonlinear filters
  • Upper bound

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