Pattern transition and bifurcation analysis of ELU-type memristive FitzHugh-Nagumo neuron

Wu Xiao, Fuhong Min, Jiakai Lu and Hailong Huo

Chaos, Solitons & Fractals, 2025, vol. 191, issue C

Abstract: The memristive neuron model exhibits complex and unpredictable dynamical behavior, especially in the transition of firing patterns, which poses significant challenges for studying the firing mechanisms of neurons. To better explore the different firing activities of memristive neurons, an ELU-type memristive FitzHugh-Nagumo neuron model based on the ELU activation function, which addresses the issue of gradient vanishing effect, is proposed firstly. The equilibrium points of the model are investigated for initial exploration, leading to the understanding of the causes of firing phenomenon and its transition. To further elucidate the firing mechanism triggered by external stimulation, an exhaustive characterization of complex bifurcation behaviors and phase trajectory is provided through a novel semi-analytical perspective, capturing the evolution of both stable and unstable firing activities, particularly the migration from unstable to stable firing patterns. Additionally, Hamilton energy derivatives with time and attractor control, such as amplification and offset-boosting controls, are applied to reflect the arbitrary relocation of the dynamics. The mode shift of unsteady and steady periodic attractors and the accuracy of implicit discrete mapping method are verified by field-programmable gate array.

Keywords: Memristive neuron model; FitzHugh-Nagumo neuron; Pattern transition; Attractor control (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096007792401467X
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:191:y:2025:i:c:s096007792401467x

DOI: 10.1016/j.chaos.2024.115915

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. ().