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

Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

686
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
686

You might also read

Related Articles

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

Sort by
Same author

Identification of shipping signals with few-shot learning: A distribution-aware approach.

PloS one·2026
Same author

Intravitreal Cidofovir Injection for Refractory End-Stage Glaucoma and Vision Loss in Silicone Oil-Filled Eyes Following Retinal Reattachment Surgery in Dogs: Four Cases.

Veterinary ophthalmology·2026
Same author

Staphylococcus Enrichment in Cutaneous Melanoma.

The Journal of dermatology·2025
Same author

Passive acoustic monitoring of sound characteristics and vocalization patterns of the brown croaker.

Biology letters·2025
Same author

Direct Access of Heteroaryl Difunctional Monomers for Arene-Enriched Polysiloxane Synthesis.

Organic letters·2025
Same author

Survey on Alopecia Areata Patients' Reported Factors that Determine Severity of Alopecia Areata: A Nationwide Multicenter Study.

Annals of dermatology·2024

Related Experiment Video

Updated: Jan 15, 2026

Synthetic, Multi-Layer, Self-Oscillating Vocal Fold Model Fabrication
10:16

Synthetic, Multi-Layer, Self-Oscillating Vocal Fold Model Fabrication

Published on: December 2, 2011

14.5K

Reconstruction Modeling and Validation of Brown Croaker (Miichthys miiuy) Vocalizations Using Wavelet-Based Inversion

Sunhyo Kim1, Jongwook Choi2, Bum-Kyu Kim1

  • 1Sea Power Reinforcement Security Research Department, Korea Institute of Ocean Science & Technology (KIOST), Busan 49111, Republic of Korea.

Sensors (Basel, Switzerland)
|October 16, 2025
PubMed
Summary
This summary is machine-generated.

This study presents a novel framework for reconstructing brown croaker (Miichthys miiuy) vocalizations using wavelet synthesis and deep learning. The method reliably generates realistic fish sounds, aiding passive acoustic monitoring (PAM) and data augmentation.

Keywords:
bioacoustic signal reconstructionbrown croaker vocalizationpassive acoustic monitoring (PAM)waveform similarity

More Related Videos

Automated Interactive Video Playback for Studies of Animal Communication
07:21

Automated Interactive Video Playback for Studies of Animal Communication

Published on: February 9, 2011

14.0K
Activity of Posterior Lateral Line Afferent Neurons during Swimming in Zebrafish
10:34

Activity of Posterior Lateral Line Afferent Neurons during Swimming in Zebrafish

Published on: February 10, 2021

4.2K

Related Experiment Videos

Last Updated: Jan 15, 2026

Synthetic, Multi-Layer, Self-Oscillating Vocal Fold Model Fabrication
10:16

Synthetic, Multi-Layer, Self-Oscillating Vocal Fold Model Fabrication

Published on: December 2, 2011

14.5K
Automated Interactive Video Playback for Studies of Animal Communication
07:21

Automated Interactive Video Playback for Studies of Animal Communication

Published on: February 9, 2011

14.0K
Activity of Posterior Lateral Line Afferent Neurons during Swimming in Zebrafish
10:34

Activity of Posterior Lateral Line Afferent Neurons during Swimming in Zebrafish

Published on: February 10, 2021

4.2K

Area of Science:

  • Bioacoustics
  • Computational Biology
  • Signal Processing

Background:

  • Fish vocalizations are crucial for passive acoustic monitoring (PAM) and ecological studies.
  • Limited high-quality recordings, especially for species like the brown croaker (Miichthys miiuy), hinder bioacoustic research.
  • Developing data-driven methods for generating realistic fish sounds is essential for advancing PAM.

Purpose of the Study:

  • To develop and validate a framework for reconstructing brown croaker vocalizations.
  • To address data limitations in bioacoustics by creating synthetic yet realistic fish sounds.
  • To enhance passive acoustic monitoring capabilities through improved species-specific call simulation.

Main Methods:

  • fk14 wavelet synthesis combined with PSO-based parameter optimization.
  • Sensitivity analysis to identify critical parameters (delay and scale) for waveform reconstruction.
  • Deep learning validation using a ResNet-18-based Siamese network for signal comparison.

Main Results:

  • Reconstructed signals closely matched measured calls in time and frequency domains, preserving morphology and spectral density.
  • Wavelet synthesis with optimized parameters maintained >98% waveform similarity within identified valid ranges.
  • Deep learning validation showed near-unity cosine similarity (~0.9996) between real and reconstructed signals.
  • Reconstruction fidelity decreased with lower signal-to-noise ratios (SNR) in noisy conditions.

Conclusions:

  • The proposed framework reliably generates acoustically realistic and morphologically consistent fish vocalizations, even with limited data.
  • This methodology is promising for dataset augmentation, enhancing PAM applications, and simulating species-specific calls.
  • Future work will leverage reconstructed signals to train generative models for scalable synthesis and real-time adaptive monitoring.