Dynamics and implementation of a functional neuron model with hyperchaotic behavior under electromagnetic radiation
Tao Ma,
Jun Mou and
Wanzhong Chen
Chaos, Solitons & Fractals, 2025, vol. 190, issue C
Abstract:
Prolonged exposure to electromagnetic radiation (EMR) may be hazardous to human health and plays a key role in the medical diagnosis of some diseases. And this effect can be better demonstrated by constructing a neuron model of EMR. Flux-controlled memristors can estimate the effects of EMR on neurons. In this work, a discrete flux-controlled memristor is used to estimate the behavior of EMR. Furthermore, the memristor is introduced into a neuron model to explore the effects of EMR on the behavior of neurons. The rich and interesting complex dynamical behavior of the model is investigated using analytical methods from nonlinear theory, including plotting bifurcation diagrams, Lyapunov exponent spectra (LEs) and complexity. By modulating the electromagnetic induction strength k of the memristor, it was observed that the introduction of EMR is able to generate hidden hyperchaotic attractors and initial-boosted behavior. The constructed neuron model is implemented based on a DSP platform. Pseudo random number generators (PRNGs) are further designed and the NIST test results illustrate the excellent random performance of the sequences generated by the neuron model. The properties exhibited in the neuron model under EMR provide a reference solution for EMR in the diagnosis and treatment of certain diseases.
Keywords: Neuron; Memristor; EMR; DSP; PRNGs (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096007792401347X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:190:y:2025:i:c:s096007792401347x
DOI: 10.1016/j.chaos.2024.115795
Access Statistics for this article
Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros
More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().