Cardiac memory phenomenon, time-fractional order nonlinear system and bidomain-torso type model in electrocardiology

Belmiloudi, Aziz

doi:10.3934/math.2021050

Cited by 3 publications

(1 citation statement)

References 69 publications

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“…Researchers from various areas has been motivated by the increasing use of fractional calculus in the mathematical modeling of processes in health sciences, natural sciences, economy and engineering (see, e.g. [11], [12], [42] and [48]). This calculus is more reliable in predicting the evolution of some phenomena or processes, such as particle motion, conservation of mass, propagation of acoustic waves and anomalous diusion in complex media.…”

Section: Introductionmentioning

confidence: 99%

Non-linear pseudo-differential evolution equation in fractional time.

Vergara Aguilar

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Section: Introductionmentioning

confidence: 99%

Non-linear pseudo-differential evolution equation in fractional time.

Vergara Aguilar

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A fast time integral finite difference method for a space-time fractional FitzHugh-Nagumo monodomain model in irregular domains

Cai,

Cao,

Jing

et al. 2024

Journal of Computational Physics

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Brain Connectivity Dynamics and Mittag–Leffler Synchronization in Asymmetric Complex Networks for a Class of Coupled Nonlinear Fractional-Order Memristive Neural Network System with Coupling Boundary Conditions

Belmiloudi

2024

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This paper investigates the long-time behavior of fractional-order complex memristive neural networks in order to analyze the synchronization of both anatomical and functional brain networks, for predicting therapy response, and ensuring safe diagnostic and treatments of neurological disorder (such as epilepsy, Alzheimer’s disease, or Parkinson’s disease). A new mathematical brain connectivity model, taking into account the memory characteristics of neurons and their past history, the heterogeneity of brain tissue, and the local anisotropy of cell diffusion, is proposed. This developed model, which depends on topology, interactions, and local dynamics, is a set of coupled nonlinear Caputo fractional reaction–diffusion equations, in the shape of a fractional-order ODE coupled with a set of time fractional-order PDEs, interacting via an asymmetric complex network. In order to introduce into the model the connection structure between neurons (or brain regions), the graph theory, in which the discrete Laplacian matrix of the communication graph plays a fundamental role, is considered. The existence of an absorbing set in state spaces for system is discussed, and then the dissipative dynamics result, with absorbing sets, is proved. Finally, some Mittag–Leffler synchronization results are established for this complex memristive neural network under certain threshold values of coupling forces, memristive weight coefficients, and diffusion coefficients.

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Cardiac memory phenomenon, time-fractional order nonlinear system and bidomain-torso type model in electrocardiology

Cited by 3 publications

References 69 publications

Non-linear pseudo-differential evolution equation in fractional time.

Non-linear pseudo-differential evolution equation in fractional time.

A fast time integral finite difference method for a space-time fractional FitzHugh-Nagumo monodomain model in irregular domains

Brain Connectivity Dynamics and Mittag–Leffler Synchronization in Asymmetric Complex Networks for a Class of Coupled Nonlinear Fractional-Order Memristive Neural Network System with Coupling Boundary Conditions

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