Differentiable Distribution Model of Stochastic Volatile Memristor-Based Neuron

Volatile memristors have received extensive attention in neuromorphic computing. It is of significance to build compact models of these devices for neuromorphic hardware design. In this work, we propose a compact model of metallic filamentary volatile memristor reproducing ideal and stochastic switc...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on electron devices 2025-02, p.1-6
Main Authors: Chen, Anzhe, Hu, Jiayang, Ma, Hanzhi, Jiang, Yining, Yu, Bin
Format: Article
Language:English
Subjects:
Compact model
Computational modeling
Electrolytes
Integrated circuit modeling
Ions
memristor neuron
Memristors
Neurons
Numerical models
spiking neural network (SNN)
stochastic behavior
Stochastic processes
Switches
Threshold voltage
volatile memristor
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Volatile memristors have received extensive attention in neuromorphic computing. It is of significance to build compact models of these devices for neuromorphic hardware design. In this work, we propose a compact model of metallic filamentary volatile memristor reproducing ideal and stochastic switching behavior in various operation schemes. We further derive the differentiable distribution model of stochastic switching, enabling co-optimization with neural network to obtain optimal operating conditions. Experiments are conducted to validate the compact model with demonstrated neuromorphic application. The compact model bridges memristive characteristics and algorithm optimization for neuromorphic computing.
ISSN:0018-9383
1557-9646
DOI:10.1109/TED.2025.3538660