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

Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

1.8K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
1.8K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.4K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.4K
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

377
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
377
Role of Shaping in Operant Conditioning01:19

Role of Shaping in Operant Conditioning

965
Shaping is a technique used in operant conditioning to train complex behaviors by rewarding successive approximations toward the target behavior. This method is necessary because organisms are unlikely to perform complex behaviors spontaneously. Instead, shaping breaks down the desired behavior into small, manageable steps.
The steps involved in shaping begin with reinforcing any response that resembles the desired behavior. For example, parents might praise a child for picking up one toy. As...
965
NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

1.0K
When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
1.0K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

10.2K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
10.2K

You might also read

Related Articles

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

Sort by
Same author

A case report of tetanus complicated by multiple cerebral infarcts and iliopsoas hematoma.

Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy·2026
Same author

Differences in contributing factors to diagnostic errors between physicians and allied health professionals: a nationwide analysis in Japan.

BMJ open quality·2025
Same author

Generation of a Rat Monoclonal Antibody for Human Nucleophosmin.

Monoclonal antibodies in immunodiagnosis and immunotherapy·2025
Same author

Pioneering diagnosis in Asia: advancing clinical reasoning expertise through the lens of 3M.

Diagnosis (Berlin, Germany)·2025
Same author

Generation of Rat Monoclonal Antibody for Human Nucleolin.

Monoclonal antibodies in immunodiagnosis and immunotherapy·2023
Same author

Generation of Rat Monoclonal Antibody for Mouse Nucleolin by Immunization of Ferroptosis-Induced Hepa 1-6 Cells.

Monoclonal antibodies in immunodiagnosis and immunotherapy·2022

Related Experiment Video

Updated: Jan 17, 2026

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

10.3K

Mitigating error enhancement of probabilistic amplitude shaping by error-correctable shaping.

Mamoru Komatsu, Yuki Nishino, Akira Naka

    Optics Express
    |September 23, 2025
    PubMed
    Summary

    Probabilistic amplitude shaping improves signal-to-noise ratio but causes burst errors. Our error-correctable ESS (E-ESS) mitigates these errors, reducing the need for strong forward-error correction codes.

    More Related Videos

    Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
    08:39

    Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

    Published on: January 28, 2019

    10.3K
    Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
    09:01

    Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

    Published on: April 4, 2017

    9.1K

    Related Experiment Videos

    Last Updated: Jan 17, 2026

    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

    10.3K
    Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
    08:39

    Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

    Published on: January 28, 2019

    10.3K
    Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
    09:01

    Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

    Published on: April 4, 2017

    9.1K

    Area of Science:

    • Optical communication systems
    • Digital signal processing

    Background:

    • Probabilistic amplitude shaping enhances signal-to-noise ratio in optical systems.
    • The distribution matcher (DM) inverse process introduces burst errors, increasing bit-error rate (BER).

    Purpose of the Study:

    • To propose and evaluate an error-correctable distribution matcher (DM) to mitigate burst errors.
    • To reduce the bit-error rate (BER) enhancement caused by burst errors in probabilistic amplitude shaping.

    Main Methods:

    • Developed an error-correctable DM using enumerative sphere shaping (ESS) and an amplitude readjusting scheme, termed E-ESS.
    • Implemented residual error detection and correction post-decoding.
    • Conducted extensive numerical simulations and performance estimations.

    Main Results:

    • E-ESS effectively reduces burst error enhancement.
    • A small shaping gap penalty was observed.
    • The error floor requirement for forward-error correction (FEC) codes is reduced.

    Conclusions:

    • E-ESS successfully mitigates burst errors in probabilistic amplitude shaping.
    • The proposed method enhances the robustness of optical communication systems.
    • E-ESS offers a viable solution for improving BER performance in high-speed optical transmissions.