Enhancing Robustness of Memristor Crossbar‐Based Spiking Neural Networks against Nonidealities: A Hybrid Approach for Neuromorphic Computing in Noisy Environments

Enhancing Robustness of Memristor Crossbar‐Based Spiking Neural Networks against Nonidealities: A Hybrid Approach for Neuromorphic Computing in Noisy Environments

Memristor crossbar‐based spiking neural networks (SNNs) face challenges caused by nonidealities associated with their hardware‐based neurons and synapses. The key nonidealities include electric‐field noise, conductance noise, and conductance drift. This study investigates the robustness of fully con...

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Bibliographic Details
Main Authors: Yafeng Zhang, Hao Sun, Mande Xie, Zhe Feng, Zuheng Wu
Format: Article
Language:English
Published: Wiley 2023-11-01
Series:Advanced Intelligent Systems
Subjects:
hybrid residual spiking neural network
memristor crossbar
neuromorphic computing
nonideality
Online Access:https://doi.org/10.1002/aisy.202300411

Internet

https://doi.org/10.1002/aisy.202300411

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