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

Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

421
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
421
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

294
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
294
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

310
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
310
Classification of Signals01:30

Classification of Signals

1.2K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.2K
Network Function of a Circuit01:25

Network Function of a Circuit

530
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.
530
Basic Discrete Time Signals01:16

Basic Discrete Time Signals

565
The unit step sequence is defined as 1 for zero and positive values of the integer n. This sequence can be graphically displayed using a set of eight sample points, showing a step function starting from n=0 and remaining constant thereafter.
The unit impulse or sample sequence is mathematically expressed as zero for all n values except at n=0, where it is one. The unit impulse sequence, denoted by δ(n), is the first difference of the unit step sequence, while the unit step sequence u(n) is the...
565

You might also read

Related Articles

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

Sort by
Same author

Narrowband-wideband boundary-guided optimal DSCM partitioning for all-order PMD compensation in high symbol rate systems.

Optics express·2026
Same author

Associations between TT-TG distance and rotational and coronal alignment in recurrent patellar dislocation.

BMC musculoskeletal disorders·2026
Same author

Assessment of the diagnostic performance and influencing factors of AFP and PIVKA-II in hepatocellular carcinoma.

Discover oncology·2026
Same author

A multifunctional EGCG/Si nanohybrid-coated 3D-printed porous scaffold for bone defect repair.

Regenerative biomaterials·2026
Same author

Inhibition of Wnt Signaling Using Axin Peptidomimetics through Direct Targeting of β-Catenin.

Journal of medicinal chemistry·2026
Same author

Pilot-aided Kalman filter scheme with high robustness for joint equalization of PMD, RSOP, and RCD in ultra-high-speed coherent fiber-optic communications systems.

Optics express·2026
Same journal

Denoising algorithm of Φ-OTDR systems based on adaptive fractional wavelet transform denoising.

Optics express·2026
Same journal

Millisecond photon-to-photon latency and high-speed volumetric projection system for optogenetics.

Optics express·2026
Same journal

Polarization-encoded coaxial structured light for high-precision 3D surface profilometry.

Optics express·2026
Same journal

Discrete freeform optical design based on collaborative optimization of point cloud and local normals.

Optics express·2026
Same journal

Ultrafast ghost imaging with 25 GHz speckle switching and wavelength-division multiplexing.

Optics express·2026
Same journal

Atomic vapor cells fabricated by femtosecond laser welding of standard-optical-quality glass.

Optics express·2026
See all related articles

Related Experiment Video

Updated: Dec 14, 2025

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

10.2K

Robust neural network receiver for multiple-eigenvalue modulated nonlinear frequency division multiplexing system.

Yue Wu, Lixia Xi, Xulun Zhang

    Optics Express
    |July 19, 2020
    PubMed
    Summary
    This summary is machine-generated.

    We developed a novel neural network (NN) receiver for nonlinear frequency division multiplexing (NFDM) systems. This NN receiver significantly improves data recovery accuracy in complex, high-capacity NFDM transmissions, outperforming traditional methods.

    More Related Videos

    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
    11:54

    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

    Published on: March 13, 2017

    9.7K
    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
    11:25

    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Published on: July 26, 2013

    43.9K

    Related Experiment Videos

    Last Updated: Dec 14, 2025

    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

    10.2K
    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
    11:54

    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

    Published on: March 13, 2017

    9.7K
    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
    11:25

    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Published on: July 26, 2013

    43.9K

    Area of Science:

    • Optical Communications
    • Signal Processing
    • Machine Learning

    Background:

    • Nonlinear frequency division multiplexing (NFDM) offers a path beyond the Kerr nonlinearity limit in optical fiber communications.
    • Increasing transmission capacity in NFDM relies on multiple-eigenvalue modulation, but this escalates signal complexity and demodulation challenges.
    • Traditional nonlinear Fourier transform (NFT) algorithms struggle with accuracy and robustness in practical NFDM systems due to noise and increased modulation orders.

    Purpose of the Study:

    • To propose and validate an innovative receiver design for multiple-eigenvalue modulated NFDM systems.
    • To enhance the demodulation accuracy and robustness of NFDM systems, particularly under channel impairments.
    • To enable the practical deployment of high-capacity NFDM systems with complex modulation formats.

    Main Methods:

    • Development of a novel receiver architecture based on regression neural networks (NNs).
    • Testing the NN receiver's performance in both single- and dual-polarization NFDM systems.
    • Comparative analysis against Nonlinear Fourier Transform (NFT) and Euclidean Minimum Distance (MD) receivers.

    Main Results:

    • The proposed NN receiver demonstrates high accuracy and robustness in demodulating information for NFDM systems.
    • Achieved a low bit error rate with 2 GBaud 16QAM modulation over 1,000 km in a four-eigenvalue modulated system.
    • The NN receiver outperforms NFT and MD receivers, especially for higher-order modulation formats and complex NFDM systems.

    Conclusions:

    • Neural network-based receivers are a viable and effective solution for overcoming the limitations of traditional methods in advanced NFDM systems.
    • The NN receiver offers significant advantages in terms of accuracy, robustness, and tolerance to channel impairments.
    • This approach paves the way for realizing the full potential of high-capacity, multi-eigenvalue modulated NFDM communication systems.