Skip navigation
Skip navigation

A Bayesian framework for geoacoustic inversion of wind-driven ambient noise in shallow water

Quijano, Jorge E.; Dosso, S.E.; Dettmer, Jan


Bayesian inversion is applied to estimate the joint posterior probability density (PPD) of geoacoustic parameters. The PPD is sampled by a reversible-jump Markov chain Monte Carlo (rjMCMC) algorithm, which uses an extended Metropolis-Hasting (MH) criterion that allows trans-D jumps between parameterizations, quantifying the uncertainly due to the lack of knowledge of the model parameterization. Sequential datsets are obtained by discretizing continuous-time recordings of ambient noise....[Show more]

CollectionsANU Research Publications
Date published: 2012
Type: Conference paper
Source: Canadian Acoustics Vol 40 - Number 3 Proceedings of the Acoustics Week in Canada 2011


File Description SizeFormat Image
01_Quijano_A_Bayesian_framework_for_2012.pdf201.56 kBAdobe PDF    Request a copy
02_Quijano_A_Bayesian_framework_for_2012.pdf103.79 kBAdobe PDF    Request a copy

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  19 May 2020/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator