High-Noise Asymptotics of the Ziv-Zakai Bound

Alex Dytso, Martina Cardone, Ian Zieder

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The Ziv-Zakai bound is a well-known lower bound on the minimum mean squared error. This article analyzes the performance of this bound in the practically relevant high-noise regime for a broad family of observation models. The goal is to understand whether this bound is tight, and in which scenarios it should be used. It is shown that, while the Ziv-Zakai bound is tight for a certain class of symmetric distributions, in general, it is not tight in the high-noise regime.

Original languageEnglish (US)
Pages (from-to)1933-1937
Number of pages5
JournalIEEE Signal Processing Letters
Volume29
DOIs
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 1994-2012 IEEE.

Keywords

  • Bayesian risk, Cramér-Rao bound, MMSE

Fingerprint

Dive into the research topics of 'High-Noise Asymptotics of the Ziv-Zakai Bound'. Together they form a unique fingerprint.

Cite this