Offset boosting-based attractor doubling of Rulkov neuron

Yongxin Li, Chunbiao Li*, Qianyuan Tang, Wanning Yu, Ming Xia

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

1 Citation (Scopus)

Abstract

The polarity adjustment of the neuronal signals plays an important role in neuron dynamics. In this work, attractor doubling is obtained through offset boosting to regulate the distance between two coexisting neuron attractors. Chaotic firings in the Rulkov neuron with flexibly-controlled average are obtained reshaping the associated phase orbits and patterns. The design of the absolute value function with proper constant provides a new method for attractor doubling with regulatable distances. This approach brings more controllability from the parameter or the initial conditions. Strikingly, the amplitude and frequency of firings can be effectively modified by the offset booster when it exceeds a certain threshold. Finally, circuit implementation based on the CH32 platform was given, which verifies the theory prediction and numerical simulations.

Original languageEnglish
Pages (from-to)14379-14392
Number of pages14
JournalNonlinear Dynamics
Volume112
Issue number16
Early online date12 Jun 2024
DOIs
Publication statusPublished - Aug 2024

Scopus Subject Areas

  • Control and Systems Engineering
  • Aerospace Engineering
  • Ocean Engineering
  • Mechanical Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

User-Defined Keywords

  • Attractor doubling
  • Chaotic map
  • Offset boosting
  • Rulkov neuron

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