Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Estimating parameter uncertainties in matched field inversion by a neighborhood approximation algorithm.

Kunde Yang1, N Ross Chapman, Yuanliang Ma

  • 1College of Oceanic Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, PR China. ykdzym@nwpu.edu.cn

The Journal of the Acoustical Society of America
|March 14, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Physics-based and data-driven joint approach for low-frequency underwater acoustic field predictiona).

The Journal of the Acoustical Society of America·2026
Same author

Optimizing partial receiver operating characteristic curve via curriculum learning and Neyman-Pearson criterion for robust underwater acoustic target detection.

The Journal of the Acoustical Society of America·2026
Same author

Accurate Deeplofargram: Accurate dynamic dim frequency line recovery for underwater acoustic target via waveform diffusion model.

The Journal of the Acoustical Society of America·2025
Same author

Angle-distance decomposition based on deep learning for active sonar detection.

The Journal of the Acoustical Society of America·2025
Same author

A Robust Bilayer Superhydrophobic Coating Based on Graphene Oxide with Integrated Photothermal Effects for Efficient Anti-/Deicing and Durability Applications.

Langmuir : the ACS journal of surfaces and colloids·2025
Same author

Target echo interference characteristic in the deep water: Modeling and application in depth estimation.

The Journal of the Acoustical Society of America·2025
Same journal

Sibilant differentiation before and after tongue cancer surgery: Acoustics, kinematics and the role of sensorimotor controla).

The Journal of the Acoustical Society of America·2026
Same journal

BioNet-A: Ultrasonic echo representation network for target discrimination using active SONAR.

The Journal of the Acoustical Society of America·2026
Same journal

Empty soft-drink cans and mass-loaded rods: Analogous homework problems from acoustic and mechanical domains.

The Journal of the Acoustical Society of America·2026
Same journal

Erratum: Statistical wave field theory: Anisotropic wave fields under Neumann's boundary condition [J. Acoust. Soc. Am. 159(3), 2265-2280 (2026)].

The Journal of the Acoustical Society of America·2026
Same journal

On the modification of tip leakage noise sources by porous treatment.

The Journal of the Acoustical Society of America·2026
Same journal

An educational opportunity: Acoustics in an empty room.

The Journal of the Acoustical Society of America·2026
See all related articles

A new Neighborhood Approximation Bayes (NAB) algorithm offers a faster alternative to the Fast Gibbs Sampler (FGS) for Bayesian inversion. This method efficiently estimates posterior probability densities (PPDs) with reduced computational cost.

Area of Science:

  • Computational Geophysics
  • Bayesian Inference
  • Geophysical Inversion

Background:

  • Bayesian inversion relies on estimating the posterior probability density (PPD).
  • Traditional methods like the Fast Gibbs Sampler (FGS) are computationally intensive, especially for complex, multi-frequency, or range-dependent problems.
  • Accurate PPD estimation is crucial for characterizing inversion solutions.

Purpose of the Study:

  • To introduce and evaluate a novel Neighborhood Approximation Bayes (NAB) algorithm as an efficient alternative for Bayesian inversion.
  • To improve the accuracy and completeness of PPD estimation in higher-dimensional or sensitive parameter inversion problems.
  • To reduce the computational burden associated with traditional inversion techniques.

Main Methods:

Related Experiment Videos

  • Developed a Neighborhood Approximation Bayes (NAB) algorithm to approximate the posterior probability density (PPD).
  • Implemented a multi-step inversion scheme that flexibly adjusts parameter search intervals based on preliminary NAB estimations.
  • Incorporated all solved forward models into the appraisal stage for PPD approximation, a key feature of NAB.

    • Main Results:

    • The NAB algorithm demonstrated effective approximation of PPDs in lower-dimensional geoacoustic inversion.
    • A multi-step scheme enhanced NAB's accuracy for higher-dimensional problems and sensitive parameters, yielding more complete parameter uncertainties.
    • NAB provided reasonable estimates of PPD moments, comparable to FGS, but with significantly reduced computation time on synthetic and real data.

    Conclusions:

    • The Neighborhood Approximation Bayes (NAB) algorithm is a computationally efficient alternative to the Fast Gibbs Sampler (FGS) for Bayesian inversion.
    • The proposed multi-step inversion scheme improves NAB's performance in complex scenarios, offering a balance between accuracy and computational cost.
    • NAB presents a viable approach for geophysical inversion, delivering reliable results with substantial time savings.