Sculpting priors

Fuente: arXiv
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Bibliographic Details
Main Author: Theiler, James
Format: Preprint
Published: 2024
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author Theiler, James
author_facet Theiler, James
contents Bayesian priors are investigated for detecting targets of known spectral signature (but unknown strength) in cluttered backgrounds. A specific problem is the construction (or ``sculpting'') of a Bayesian prior that uniformly outperforms its non-Bayesian counterpart, the nominally sub-optimal but widely used Generalized Likelihood Ratio Test (GLRT).
format Preprint
id arxiv_https___arxiv_org_abs_2408_04572
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Sculpting priors
Theiler, James
Signal Processing
Statistics Theory
62C10
G.3
Bayesian priors are investigated for detecting targets of known spectral signature (but unknown strength) in cluttered backgrounds. A specific problem is the construction (or ``sculpting'') of a Bayesian prior that uniformly outperforms its non-Bayesian counterpart, the nominally sub-optimal but widely used Generalized Likelihood Ratio Test (GLRT).
title Sculpting priors
topic Signal Processing
Statistics Theory
62C10
G.3
url https://arxiv.org/abs/2408.04572