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Related Concept Videos

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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¹H NMR: Complex Splitting01:13

¹H NMR: Complex Splitting

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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Related Experiment Video

Updated: Jun 7, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Improved linear programming method to generate metameric spectral distributions.

J M Zoido, F Carreño, E Bernabeu

    Applied Optics
    |November 2, 2010
    PubMed
    Summary
    This summary is machine-generated.

    Linear programming generates metameric spectral distributions for color stimuli. This method allows for creating numerous spectral power distributions with specific physical color properties, dominant wavelength, and high excitation purity across various brightness levels.

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    ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
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    Published on: March 14, 2013

    Area of Science:

    • Color Science
    • Photometry
    • Computational Optics

    Background:

    • Metameric spectral radiant power distributions are crucial for color matching and display technology.
    • Generating these distributions under specific physical constraints remains a challenge.

    Purpose of the Study:

    • To apply linear programming for generating metameric spectral radiant power distributions.
    • To establish criteria for distributions associated with high-excitation purity color stimuli at any brightness.

    Main Methods:

    • Utilized linear-programming techniques to model and solve for spectral power distributions.
    • Incorporated constraints related to physical color properties, dominant wavelength, and excitation purity.

    Main Results:

    • Successfully generated metameric spectral radiant power distributions meeting specified criteria.
    • Demonstrated the ability to achieve high-excitation purity values across a range of brightness levels.
    • Showcased that an unlimited number of metameric distributions can be derived.

    Conclusions:

    • Linear programming offers a robust framework for generating metameric spectral distributions.
    • The proposed criteria enable precise control over color stimulus properties like dominant wavelength and excitation purity.
    • This approach provides flexibility in creating diverse spectral distributions for various applications.