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

Aliasing01:18

Aliasing

119
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
119
IR Frequency Region: X–H Stretching01:24

IR Frequency Region: X–H Stretching

914
In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of  2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in...
914
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

762
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
762
Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

194
Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used....
194
Characteristics of OpAmp01:17

Characteristics of OpAmp

608
The operational amplifier, commonly known as an op-amp, is a specially designed electronic circuit component. Its purpose is to work in conjunction with other circuit elements to execute a defined signal-processing operation. Consider an equivalent circuit model of an op-amp, as depicted in Figure 1; the output section comprises a voltage-controlled source in parallel with the output resistance Ro.
608

You might also read

Related Articles

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

Sort by
Same author

Three-dimensional markerless motion capture of multiple freely behaving monkeys toward automated characterization of social behavior.

Science advances·2025
Same author

A Novel Snow Leopard Optimization for High-Dimensional Feature Selection Problems.

Sensors (Basel, Switzerland)·2024
Same author

Integrated Control of Thermal Residual Stress and Mechanical Properties by Adjusting Pulse-Wave Direct Energy Deposition.

Materials (Basel, Switzerland)·2024
Same author

A cosine adaptive particle swarm optimization based long-short term memory method for urban green area prediction.

PeerJ. Computer science·2024
Same author

A deep memory bare-bones particle swarm optimization algorithm for single-objective optimization problems.

PloS one·2023
Same author

An electronic transition-based bare bones particle swarm optimization algorithm for high dimensional optimization problems.

PloS one·2022
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: Jun 6, 2025

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.8K

Advanced Modulation Formats for 400 Gbps Optical Networks and AI-Based Format Recognition.

Zhou He1,2, Hao Huang3, Fanjian Hu4

  • 1Hubei Key Laboratory of Digital Finance Innovation, Hubei University of Economics, Wuhan 430205, China.

Sensors (Basel, Switzerland)
|November 27, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel noncoherent optical network solution using Apol-CRZ-FSK modulation for integrated communication and sensing. It demonstrates superior performance against nonlinear effects and high accuracy in modulation format identification.

Keywords:
convolutional neural network (CNN)integration of communication and sensing (ICAS)modulation formatmodulation format identification (MFI)optical networks

More Related Videos

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

9.8K
Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution
08:48

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Published on: September 5, 2012

11.8K

Related Experiment Videos

Last Updated: Jun 6, 2025

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

10.8K
Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

9.8K
Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution
08:48

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Published on: September 5, 2012

11.8K

Area of Science:

  • Optical networking
  • Integrated communication and sensing (ICAS)
  • Signal processing

Background:

  • Optical networks are evolving towards integrating communication and sensing (ICAS) for intelligent systems.
  • Co-fiber transmission of communication and sensing signals causes nonlinear interference, increasing bit error rate (BER).

Purpose of the Study:

  • To propose and evaluate a noncoherent solution for 4 × 100 Gbps DWDM optical networks supporting ICAS.
  • To enhance signal transmission performance and enable reliable signal sensing and recognition.

Main Methods:

  • Utilizing the alternate polarization chirped return-to-zero frequency shift keying (Apol-CRZ-FSK) modulation format.
  • Employing the Inception-ResNet-v2 convolutional neural network for modulation format identification.

Main Results:

  • The Apol-CRZ-FSK solution shows superior resistance to nonlinear effects compared to CRZ-FSK and DQPSK.
  • The Inception-ResNet-v2 model achieved the highest performance in identifying three modulation formats among seven deep learning methods.

Conclusions:

  • The proposed Apol-CRZ-FSK modulation offers a low-cost, high-performance solution for ICAS optical networks.
  • The study provides an effective method for signal recognition in future high-speed optical networks.