Fractal Analysis of High-Performance Parallel Architectures for Nonlinear Cardiac Models

In this study, we develop parallel techniques for solving nonlinear equations arising in cardiac modeling, which are often computationally challenging due to their complexity and sensitivity. The proposed parallel scheme achieves a convergence order of [Formula: see text], where [Formula: see text] is a fractional parameter. Several cardiac models are employed to evaluate the efficiency, accuracy, and stability of the method. A detailed fractal analysis of the developed schemes is also presented, providing deeper insights into their dynamical behavior. Numerical results demonstrate that the proposed approach outperforms classical methods in terms of convergence rate, residual error, and stability. This work highlights the potential of fractional parallel solvers to more effectively capture complex cardiac dynamics and contribute to advanced biomedical computations.

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Publication Details

Journal
Fractals
Published
2026-05-28
DOI
https://doi.org/10.1142/s0218348x26400840
Primary Topic
Numerical methods for differential equations
Type
article
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article

Fractal Analysis of High-Performance Parallel Architectures for Nonlinear Cardiac Models

Mudassir Shams, Mdi Begum Jeelani, Ghaliah Alhamzi, Nasreen Kausar et al.
Fractals
Numerical methods for differential equations
article

Fractal Analysis of High-Performance Parallel Architectures for Nonlinear Cardiac Models

Mudassir Shams, Mdi Begum Jeelani, Ghaliah Alhamzi, Nasreen Kausar, Ali Akgul
article en

Abstract

In this study, we develop parallel techniques for solving nonlinear equations arising in cardiac modeling, which are often computationally challenging due to their complexity and sensitivity. The proposed parallel scheme achieves a convergence order of [Formula: see text], where [Formula: see text] is a fractional parameter. Several cardiac models are employed to evaluate the efficiency, accuracy, and stability of the method. A detailed fractal analysis of the developed schemes is also presented, providing deeper insights into their dynamical behavior. Numerical results demonstrate that the proposed approach outperforms classical methods in terms of convergence rate, residual error, and stability. This work highlights the potential of fractional parallel solvers to more effectively capture complex cardiac dynamics and contribute to advanced biomedical computations.

Fractals
Openalex Percentile: Top 5%
Numerical methods for differential equations
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