Jove
Visualize
Contact Us

Related Experiment Videos

Contrast source inversion methods in elastodynamics.

George Pelekanos1, Aria Abubakar, Peter M van den Berg

  • 1Department of Mathematics and Statistics, Southern Illinois University, Edwardsville, Illinois 62026, USA.

The Journal of the Acoustical Society of America
|December 3, 2003
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

Three Dimensional Microwave Data Inversion in Feature Space for Stroke Imaging.

IEEE transactions on medical imaging·2023
Same author

Deep feature-domain matching for cardiac-related component separation from a chest electrical impedance tomography image series: proof-of-concept study.

Physiological measurement·2022
Same author

Supervised Descent Learning for Thoracic Electrical Impedance Tomography.

IEEE transactions on bio-medical engineering·2020
Same author

Neural network-based supervised descent method for 2D electrical impedance tomography.

Physiological measurement·2020
Same author

Study on 3-D Acoustic Imaging for Human Thorax Based on Contrast Source Inversion.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control·2020
Same author

Ultrasonic Synthetic-Aperture Interface Imaging.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control·2019
Same journal

High-resolution depth estimation for multiple wideband sources in deep sea via sparse Bayesian learninga).

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

Depression markers in speech: An approach based on tract variables dynamics.

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

The oyster toadfish (Opsanus tau) alters active and diurnal calling amid vessel noise in New York City.

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

Experimental noise characterisation of phase-locked tandem-rotor in edgewise flight.

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

The tune-text-temporal synergy: Prosodic effects of final segmental weakening in Neapolitan.

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

Monitoring vessel movement above critical offshore infrastructure using distributed acoustic sensing.

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

This study introduces a new nonlinear inversion method to determine the mass density of elastic inclusions using scattered elastic waves. The advanced algorithm effectively handles noisy data and preserves edges in complex elastodynamic inverse scattering problems.

Area of Science:

  • Geophysics
  • Applied Mathematics
  • Materials Science

Background:

  • Determining material properties of inclusions is crucial in various scientific fields.
  • Inverse scattering problems are challenging due to ill-posedness and noise.
  • Existing methods often struggle with complex elastic wave interactions.

Purpose of the Study:

  • To present a novel nonlinear inversion method for elastic inclusion mass density retrieval.
  • To extend the multiplicative regularized contrast source inversion (MR-CSI) method to elastodynamics.
  • To demonstrate the method's effectiveness in handling noisy and complex scattering data.

Main Methods:

  • Nonlinear inversion using an extension of the MR-CSI algorithm.
  • Iterative determination of mass density contrast and contrast sources.

Related Experiment Videos

  • Incorporation of an additional regularization term as a multiplicative constraint.
  • Main Results:

    • The MR-CSI method successfully determines the mass density of elastic inclusions.
    • The algorithm exhibits excellent edge-preserving properties.
    • Robust performance is demonstrated even with noisy data in complex elastodynamic scenarios.

    Conclusions:

    • The presented MR-CSI method is highly effective for elastodynamic inverse scattering problems.
    • This approach offers a robust solution for characterizing elastic inclusions.
    • The method shows significant potential for geophysical and material science applications.