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 Concept Videos

Echo01:06

Echo

470
The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...
470

You might also read

Related Articles

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

Sort by
Same author

Equalizing the In-Ear Acoustic Response of Piezoelectric MEMS Loudspeakers Through Inverse Transducer Modeling.

Micromachines·2025
Same author

A neural network-based method for spruce tonewood characterization.

The Journal of the Acoustical Society of America·2023
Same author

On the Virtualization of Audio Transducers.

Sensors (Basel, Switzerland)·2023
Same author

A comparative analysis of the directional sound radiation of historical violins.

The Journal of the Acoustical Society of America·2022
Same author

Deep Prior Approach for Room Impulse Response Reconstruction.

Sensors (Basel, Switzerland)·2022
Same author

A Physics-Informed Neural Network Approach for Nearfield Acoustic Holography.

Sensors (Basel, Switzerland)·2021
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: May 14, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

5.1K

Diffusion-Based Sound Source Localization Using a Distributed Network of Microphone Arrays.

Davide Albertini1, Alberto Bernardini1, Gioele Greco1

  • 1Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy.

Sensors (Basel, Switzerland)
|April 12, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a distributed optimization approach for 3D sound source localization (SSL) using microphone arrays. The proposed method enhances accuracy and stability, even in sparsely connected networks, by adaptively penalizing underperforming arrays.

Keywords:
ATC diffusionmicrophone array processingsound source localizationwireless acoustic sensor networks

More Related Videos

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.6K
Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface
06:14

Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface

Published on: July 30, 2020

4.8K

Related Experiment Videos

Last Updated: May 14, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

5.1K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.6K
Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface
06:14

Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface

Published on: July 30, 2020

4.8K

Area of Science:

  • Acoustics and Signal Processing
  • Distributed Systems
  • Optimization Theory

Background:

  • Traditional microphone array networks for 3D sound source localization (SSL) often depend on centralized data processing, posing challenges to scalability and robustness.
  • Existing methods may struggle with network connectivity and varying acoustic conditions like reverberation and signal-to-noise ratio (SNR).

Purpose of the Study:

  • To reformulate 3D sound source localization (SSL) as a distributed optimization problem for enhanced network performance.
  • To introduce and evaluate a computationally distributed Adapt-Then-Combine (ATC) strategy for microphone array networks.
  • To develop adaptive cooperation strategies that improve localization accuracy by penalizing underperforming arrays.

Main Methods:

  • Recasting 3D SSL with microphone array networks as a distributed optimization problem.
  • Implementing a computationally distributed Adapt-Then-Combine (ATC) diffusion strategy.
  • Developing adaptive cooperation strategies using error-based and distance-based penalties for array performance.
  • Evaluating performance in simulated acoustic environments with varying reverberation and SNR levels.

Main Results:

  • The proposed distributed ATC approach achieves high localization accuracy and stability.
  • Adaptive cooperation strategies effectively penalize detrimental array contributions, improving overall performance.
  • The method demonstrates robustness even in sparsely connected networks.

Conclusions:

  • A distributed optimization framework offers a scalable and robust solution for 3D sound source localization.
  • Adaptive cooperation strategies are crucial for optimizing performance in decentralized microphone array systems.
  • The presented approach maintains accuracy and stability across diverse acoustic conditions and network topologies.