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Related Experiment Video

Updated: Oct 27, 2025

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
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Novel approach to solve singularly perturbed boundary value problems with negative shift parameter.

Gemechis File Duressa1

  • 1Department of Mathematics, Jimma University, Jimma, P.O. Box 378, Ethiopia.

Heliyon
|July 21, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel numerical method for singularly perturbed boundary value problems. The method accurately solves differential difference equations exhibiting boundary layer behavior, outperforming classical approaches.

Keywords:
Delay differential equationsFinite difference methodSingular perturbation problem

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Area of Science:

  • Numerical Analysis
  • Differential Equations

Background:

  • Singularly perturbed boundary value problems with negative shift parameters are differential difference equations.
  • These problems exhibit boundary layer behavior, posing challenges for traditional numerical methods.

Purpose of the Study:

  • To develop a novel and simple numerical method for solving singularly perturbed boundary value problems with negative shift parameters.
  • To address the limitations of classical numerical methods in accurately approximating solutions within boundary layers.

Main Methods:

  • A new numerical method is proposed for approximating solutions.
  • The method is designed to handle the specific characteristics of these differential difference equations.

Main Results:

  • The developed method provides accurate solutions, particularly in the inner boundary layer region.
  • It overcomes the failure of classical methods to yield smooth solutions in critical areas.
  • The method is proven to be point-wise uniformly convergent.

Conclusions:

  • The novel numerical method offers a superior approach for solving singularly perturbed boundary value problems with negative shift parameters.
  • It achieves a second-order rate of convergence, enhancing accuracy and reliability.