Toward Memristive Phase‐Change Neural Network with High‐Quality Ultra‐Effective Highly‐Self‐Adjustable Online Learning

Toward Memristive Phase‐Change Neural Network with High‐Quality Ultra‐Effective Highly‐Self‐Adjustable Online Learning

Abstract Memristive hardware with reconfigurable conductance levels are leading candidates for achieving artificial neural networks (ANNs). However, owing to difficulties in device character design and circuit combination, the ability to perform complicated online‐learning tasks on a memristive netw...

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Bibliographic Details
Main Authors: Kian‐Guan Lim, Shao‐Xiang Go, Chun‐Chia Tan, Yu Jiang, Kui Cai, Tow‐Chong Chong, Stephen R. Elliott, Tae‐Hoon Lee, Desmond K. Loke
Format: Article
Language:English
Published: Wiley-VCH 2024-03-01
Series:Advanced Physics Research
Subjects:
artificial neural network
image classification
in situ online learning
memristive devices
phase‐change‐memory materials
Online Access:https://doi.org/10.1002/apxr.202300085

Internet

https://doi.org/10.1002/apxr.202300085

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