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

Wave Parameters01:10

Wave Parameters

9.6K
The simplest mechanical waves are associated with simple harmonic motion and repeat themselves for several cycles. These simple harmonic waves can be modeled using a combination of sine and cosine functions. Consider a simplified surface water wave that moves across the water's surface. Unlike complex ocean waves, in surface water waves, water moves vertically, oscillating up and down, whereas the disturbance of the wave moves horizontally through the medium. If a seagull is floating on the...
9.6K
Deconvolution01:20

Deconvolution

683
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
683
Downsampling01:20

Downsampling

771
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
771
Sound as Pressure Waves01:17

Sound as Pressure Waves

4.8K
Sound waves, which are longitudinal waves, can be modeled as the displacement amplitude varying as a function of the spatial and temporal coordinates. As a column of the medium is displaced, its successive columns are also displaced. As the successive displacements differ relatively, a pressure difference with the surrounding pressure is created. The gauge pressure varies across the medium.
The pressure fluctuation depends on the difference in displacements between the successive points in the...
4.8K
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

830
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
830
Sound Waves: Interference00:53

Sound Waves: Interference

5.1K
Sound waves can be modeled either as longitudinal waves, wherein the molecules of the medium oscillate around an equilibrium position, or as pressure waves. When two identical waves from the same source superimpose on each other, the combination of two crests or two troughs results in amplitude reinforcement known as constructive interference. If two identical waves, that are initially in phase, become out of phase because of different path lengths, the combination of crests with troughs...
5.1K

You might also read

Related Articles

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

Sort by
Same author

Tokens enable cooperation without identification or memory.

Proceedings. Biological sciences·2026
Same author

<i>ATG16L1</i> and <i>OPTN</i> as a novel prognostic gene expression signature in acute myeloid leukemia survival.

Frontiers in oncology·2026
Same author

Altered mitochondrial ultrastructure in salivary epithelial cells of patients with Sjögren's disease is associated with mitochondrial DNA release and increased activation of pattern recognition receptors: potential use of tofacitinib as therapy.

Annals of the rheumatic diseases·2026
Same author

Vaporesponsive Lanthanide Metal-Organic Frameworks as Selective Luminescent Spin Quantum Sensors for Biogenic Amines.

Inorganic chemistry·2025
Same author

Neuropathy Progression in Acquired Amyloidosis After Domino Liver Transplantation.

Journal of the peripheral nervous system : JPNS·2025
Same author

Integrated stress response inhibition restores hsa-miR-145-5p levels after IFN-β stimulation in salivary gland epithelial cells. Association between cellular stress and miRNA biogenesis in Sjögren's disease.

Journal of autoimmunity·2025
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Mar 26, 2026

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling
06:04

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling

Published on: January 17, 2025

1.8K

Birdsong Denoising Using Wavelets.

Nirosha Priyadarshani1, Stephen Marsland1, Isabel Castro2

  • 1School of Engineering and Advanced Technology, Massey University, Palmerston North, New Zealand.

Plos One
|January 27, 2016
PubMed
Summary
This summary is machine-generated.

This study presents a novel birdsong denoising method using wavelet packet decomposition and filtering. The technique significantly improves noise reduction for automated birdsong recognition in field recordings.

More Related Videos

Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging
07:15

Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging

Published on: July 11, 2025

3.8K
Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice
08:51

Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice

Published on: May 10, 2019

12.5K

Related Experiment Videos

Last Updated: Mar 26, 2026

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling
06:04

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling

Published on: January 17, 2025

1.8K
Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging
07:15

Transient Optical Clearing Using Absorbing Molecules for Ex Vivo and In Vivo Imaging

Published on: July 11, 2025

3.8K
Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice
08:51

Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice

Published on: May 10, 2019

12.5K

Area of Science:

  • Bioacoustics
  • Signal Processing
  • Ecological Monitoring

Background:

  • Automated birdsong recording is crucial for global bird population monitoring.
  • Unattended recordings often suffer from low signal-to-noise ratios due to environmental and technical noise.
  • Robust automated birdsong recognition is essential for accurate ecological data.

Purpose of the Study:

  • To develop an effective method for denoising birdsong recordings.
  • To improve the accuracy of automated birdsong recognition systems.
  • To address the challenge of low signal-to-noise ratios in field recordings.

Main Methods:

  • A denoising approach combining wavelet packet decomposition and band-pass/low-pass filtering was developed.
  • The method was applied to automatically recorded birdsong data.
  • Performance was evaluated on natural, noisy bird recordings.

Main Results:

  • The proposed method achieved an order of magnitude improvement in noise reduction.
  • Significant enhancement in signal quality was observed in processed recordings.
  • The denoising technique proved effective against various noise sources.

Conclusions:

  • The developed denoising method offers a substantial advancement for automated birdsong analysis.
  • This technique can enhance the reliability of birdsong monitoring and population studies.
  • Improved signal clarity facilitates more accurate ecological assessments.