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Difference Scheme for Differential-Difference Problems with Small Shifts Arising in Computational Model of Neuronal Variability

Difference Scheme for Differential-Difference Problems with Small Shifts Arising in Computational... AbstractThe solution of differential-difference equations with small shifts having layer behaviour is the subject of this study. A difference scheme is proposed to solve this equation using a non-uniform grid. With the non-uniform grid, finite - difference estimates are derived for the first and second-order derivatives. Using these approximations, the given equation is discretized. The discretized equation is solved using the tridiagonal system algorithm. Convergence of the scheme is examined. Various numerical simulations are presented to demonstrate the validity of the scheme. In contrast to other techniques, maximum errors in the solution are organized to support the method. The layer behaviour in the solutions of the examples is depicted in graphs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Applied Mechanics and Engineering de Gruyter

Difference Scheme for Differential-Difference Problems with Small Shifts Arising in Computational Model of Neuronal Variability

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Publisher
de Gruyter
Copyright
© 2022 Mamatha Kodipaka et al., published by Sciendo
eISSN
2353-9003
DOI
10.2478/ijame-2022-0007
Publisher site
See Article on Publisher Site

Abstract

AbstractThe solution of differential-difference equations with small shifts having layer behaviour is the subject of this study. A difference scheme is proposed to solve this equation using a non-uniform grid. With the non-uniform grid, finite - difference estimates are derived for the first and second-order derivatives. Using these approximations, the given equation is discretized. The discretized equation is solved using the tridiagonal system algorithm. Convergence of the scheme is examined. Various numerical simulations are presented to demonstrate the validity of the scheme. In contrast to other techniques, maximum errors in the solution are organized to support the method. The layer behaviour in the solutions of the examples is depicted in graphs.

Journal

International Journal of Applied Mechanics and Engineeringde Gruyter

Published: Mar 1, 2022

Keywords: non-uniform grid; differential-difference equation; boundary layer

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