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Offset Boosting-Entangled Complex Dynamics in the Memristive Rulkov Neuron

  • Yongxin Li
  • , Chunbiao Li*
  • , Tengfei Lei
  • , Yong Yang
  • , Guanrong Chen
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

A discrete memristor is introduced into the Rulkov neuron to mimic biological neuronal synapse and modify firing dynamics. In the memristive Rulkov neuron, chaotic firing with local amplitude control is obtained, where the range of chaotic bursting can be modified by two independent controllers. These two independent bifurcation parameters provide direct amplitude/frequency control. Furthermore, offset boosting-entangled complex dynamics are captured, where the initial condition of the membrane potential can visit any of the self-reproducing attractors and even modify the complex firing, indicating the coexistence of homogeneous and heterogeneous multistabilities. Consequently, a CH32-based circuit is developed to verify various firing activities. The pseudo-random number generator results are explored based on the National Institute of Standards and Technology showing its higher performance in secure optical communication, which is further proved in the seven-core 2-km communication setup.

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Original languageEnglish
Pages (from-to)9569-9579
JournalIEEE Transactions on Industrial Electronics
Volume71
Issue number8
Online published1 Nov 2023
DOIs
Publication statusPublished - Aug 2024

Research Keywords

  • Discrete memristor
  • firing multistability
  • geometric control
  • Rulkov neuron model

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