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Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism
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A predefined-time neurodynamic model for solving absolute value equation.

Xin-Mei Lv1, Shu-Xin Miao1

  • 1College of Mathematics and Statistics, Northwest Normal University, Lanzhou, 730070, PR China.

Neural Networks : the Official Journal of the International Neural Network Society
|April 22, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a new neurodynamic model for solving absolute value equations. The model offers predefined-time convergence and robust performance against noise, outperforming existing methods.

Keywords:
Absolute value equationDynamic modelPredefined-time convergenceRobustness

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Area of Science:

  • Neurodynamics
  • Applied Mathematics
  • Control Theory

Background:

  • Absolute value equations are fundamental in various scientific and engineering fields.
  • Existing models often lack flexibility in convergence time and robustness to noise.

Purpose of the Study:

  • To develop a novel neurodynamic model for solving absolute value equations.
  • To enable flexible preset convergence times.
  • To enhance robustness against noise.

Main Methods:

  • Introduction of a universal lemma for predefined-time convergence.
  • Development and theoretical analysis of a new neurodynamic model.
  • Validation through two numerical experiments.

Main Results:

  • The proposed model converges to the exact solution within a predefined time.
  • Demonstrated strong robustness against bounded vanishing and non-vanishing noise.
  • Numerical experiments confirmed superior convergence speed and robustness.

Conclusions:

  • The new neurodynamic model provides an efficient and robust solution for absolute value equations.
  • The model's ability to preset convergence time offers practical advantages.
  • This work advances the field of neurodynamic systems for equation solving.