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Article detail · 2023

A generalized Caputo-type fractional-order neuron model under the electromagnetic field

YÖKSİS OpenAlex Open access · hybrid SJR Q2 JCR Q1 Citations 11 Percentile 78.5% FWCI 1.38
Year
2023
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue International Journal of Dynamics and Control
  • Catalog match (ISSN) International Journal of Dynamics and Control
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

Abstract This article considers a fractional-order neuron model under an electromagnetic field in terms of generalized Caputo fractional derivatives. The motivation for incorporating fractional derivatives in the previously proposed integer-order neuron model is that the fractional-order model impresses with efficient effects of the memory, and parameters with fractional orders can increase the model performance by amplifying a degree of freedom. The results on the uniqueness of the solution for the proposed neuron model are established using well-known theorems. The given model is numerically solved by using a generalized version of the Euler method with stability and error analysis. Several graphical simulations are performed to capture the variations in the membrane potential considering no electromagnetic field effects, various frequency brands of external forcing current, and the amplitude and frequency of the external magnetic radiation. The impacts of fractional-order cases are clearly justified.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

11 citations

OpenAlex cited_by_count (cache / database)

1 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

  1. A fractional-order improved FitzHugh–Nagumo neuron model 2025 Citations 6 · OpenAlex

Authors

  1. Pushpendra Kumar
  2. VEDAT SUAT ERTÜRK ONDOKUZ MAYIS ÜNİVERSİTESİ
  3. Swati Tyagi
  4. Jozef Banas
  5. A. Manickam