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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.
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Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
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Related Experiment Video

Updated: Mar 21, 2026

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention
04:32

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention

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Exploiting relative transfer function for source localization in underwater acoustics.

Baptiste Menetrier1, Abdel-Ouahab Boudraa1, G Bazile Kinda1,2

  • 1Institut de Recherche et d'Études Navales (IRENav), CC 600, Brest Cedex 9, 29240, France.

JASA Express Letters
|March 20, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a new passive source localization method using relative transfer functions for improved accuracy. The technique enhances replica uniqueness, outperforming conventional cross-correlation methods in simulations and real-world tests.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Oceanography

Background:

  • Passive source localization is crucial for underwater acoustics.
  • Matched field processing (MFP) faces challenges due to replica mismatch.
  • Data-derived replicas offer a potential solution to MFP limitations.

Purpose of the Study:

  • To investigate the use of relative transfer functions (RTF) for passive source localization.
  • To enhance the uniqueness and robustness of data-derived replicas.
  • To compare the RTF-based method with conventional cross-correlation techniques.

Main Methods:

  • Utilizing relative transfer functions as the localization feature within a data-derived replica framework.
  • Evaluating performance using normal mode simulations.
  • Assessing feasibility with controlled in situ data.

Main Results:

  • The RTF-based method demonstrates improved performance compared to conventional approaches.
  • Enhanced replica uniqueness leads to greater robustness against spectral differences.
  • Successful validation using both simulated and real-world acoustic data.

Conclusions:

  • Relative transfer functions provide a robust feature for data-derived replica-based passive source localization.
  • This approach effectively mitigates mismatch issues inherent in traditional MFP.
  • The method shows practical feasibility for underwater acoustic applications.