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

Upsampling01:22

Upsampling

330
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
330
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

131
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
131
Echo01:06

Echo

614
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,...
614

You might also read

Related Articles

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

Sort by
Same author

Spatiotemporal predictive modeling for coastal phytoplankton based on the Tapnet model: A case study in Zhejiang, China.

Marine pollution bulletin·2026
Same author

On-demand Doppler-offset beamforming with intelligent spatiotemporal metasurfaces.

Nanophotonics (Berlin, Germany)·2024
Same author

Development of SPEEK-Coated IrO<sub></sub> Sensor for High-Biomass Aquatic pH Monitoring.

ACS sensors·2024
Same author

Monitoring ocean currents during the passage of Typhoon Muifa using optical-fiber distributed acoustic sensing.

Nature communications·2024
Same author

Age, source, and future risk of COVID-19 infections in two settings of Hong Kong and Singapore.

BMC research notes·2020
Same author

Combating the Coronavirus Pandemic: Early Detection, Medical Treatment, and a Concerted Effort by the Global Community.

Research (Washington, D.C.)·2020

Related Experiment Video

Updated: Sep 21, 2025

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

3.2K

Adaptive equalization based on dynamic compressive sensing for single-carrier multiple-input multiple-output

Zhen Qin1, Jun Tao1, Fengzhong Qu2

  • 1Key Laboratory of Underwater Acoustic Signal Processing of the Ministry of Education, School of Information Science and Engineering, Southeast University, Nanjing 210096, China.

The Journal of the Acoustical Society of America
|June 1, 2022
PubMed
Summary

This study introduces a new partial-tap direct adaptive equalizer (DAE) using dynamic compressed sensing (DCS) for underwater acoustic communications. The proposed SpAdOMP-IPAPA-DAE offers reduced complexity and improved performance compared to prior methods.

More Related Videos

Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging
04:54

Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging

Published on: June 16, 2023

3.2K
Microparticle Manipulation by Standing Surface Acoustic Waves with Dual-frequency Excitations
06:51

Microparticle Manipulation by Standing Surface Acoustic Waves with Dual-frequency Excitations

Published on: August 21, 2018

7.1K

Related Experiment Videos

Last Updated: Sep 21, 2025

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements
09:36

Continuous-Wave Propagation Channel-Sounding Measurement System - Testing, Verification, and Measurements

Published on: June 25, 2021

3.2K
Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging
04:54

Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging

Published on: June 16, 2023

3.2K
Microparticle Manipulation by Standing Surface Acoustic Waves with Dual-frequency Excitations
06:51

Microparticle Manipulation by Standing Surface Acoustic Waves with Dual-frequency Excitations

Published on: August 21, 2018

7.1K

Area of Science:

  • Signal Processing
  • Underwater Acoustic Communications
  • Adaptive Filtering

Background:

  • Direct adaptive equalizers (DAE) leverage sparsity for performance and complexity benefits in underwater acoustic communications.
  • Existing partial-tap DAE designs struggle with performance degradation in severe underwater environments due to assumptions of slowly varying sparse structures.
  • Complexity reduction in DAEs, particularly through partial-tap designs, remains an area needing further research.

Purpose of the Study:

  • To address the limitations of existing partial-tap DAEs in severe underwater environments.
  • To propose and evaluate an enhanced dynamic compressed sensing (DCS)-based DAE design.
  • To achieve lower complexity and better performance in underwater acoustic communication systems.

Main Methods:

  • Development of a partial-tap DAE utilizing dynamic compressed sensing (DCS).
  • Introduction of the sparse adaptive subspace pursuit-improved proportionate affine projection algorithm (SpAdOMP-IPAPA) for symbol-wise updating of significant coefficients.
  • Comparison of the proposed SpAdOMP-IPAPA-DAE with the previous SpAdOMP-APA-DAE through experimental validation.

Main Results:

  • The proposed SpAdOMP-IPAPA-DAE demonstrates significantly lower complexity compared to the SpAdOMP-APA-DAE.
  • Experimental results confirm superior performance of the SpAdOMP-IPAPA-DAE in underwater acoustic communication scenarios.
  • The SpAdOMP-IPAPA-DAE effectively handles dynamic sparse structures, improving robustness in challenging environments.

Conclusions:

  • The enhanced DCS-based DAE, SpAdOMP-IPAPA-DAE, provides a more effective solution for complexity reduction and performance enhancement in single-carrier underwater acoustic communications.
  • The proposed algorithm successfully balances complexity and performance, outperforming previous DCS-based approaches.
  • This work advances the field of adaptive equalization for robust underwater acoustic communication systems.