Noise-induced homeostasis in memristor-based neuromorphic systems

Research output: Contribution to journal › Research article › Contributed › peer-review

Contributors

  • E. Salvador - , Autonomous University of Barcelona (Author)
  • Rosana Rodriguez Martinez - , Autonomous University of Barcelona (Author)
  • E. Miranda - , Autonomous University of Barcelona (Author)
  • J. Martin-Martinez - , Autonomous University of Barcelona (Author)
  • Antonio Rubio - , UPC Polytechnic University of Catalonia (Barcelona Tech) (Author)
  • A. Crespo-Yepes - , Autonomous University of Barcelona (Author)
  • V. Ntinas - , Chair of Fundamentals of Electrical Engineering, UPC Polytechnic University of Catalonia (Barcelona Tech) (Author)
  • G. Ch Sirakoulis - , Democritus University of Thrace (Author)
  • M. Nafria - , Autonomous University of Barcelona (Author)

Abstract

In this work, it is experimentally demonstrated that noise can be used to emulate the biological homeostatic neuron property in memristor-based neuromorphic systems. The addition of an external noise to the bias allows regulating the memristor performance when used as an artificial neuron, controlling the firing process through the modulation of the memristor threshold voltages. Experimental results have been correctly addressed using the Dynamic Memdiode Model (DMM) for memristors in the framework of SPICE simulation.

Details

Original languageEnglish
Pages (from-to)1
Number of pages1
JournalIEEE electron device letters
Volume45
Issue number8
Publication statusPublished - 2024
Peer-reviewedYes

External IDs

Mendeley f52f5300-565a-37a3-9509-a0ccb9c9439f
ORCID /0000-0002-2367-5567/work/168720269

Keywords

ASJC Scopus subject areas

Keywords

  • homeostasis, Homeostasis, Memristor, Memristors, Neuromorphics, Neurons, Noise, resistive switching, RRAM, SPICE, spike neural networks, Standards, stochastic resonance, Threshold voltage