Efficient and self-adaptive in-situ learning in multilayer memristor neural networks

Efficient and self-adaptive in-situ learning in multilayer memristor neural networks

Memristor-based neural networks hold promise for neuromorphic computing, yet large-scale experimental execution remains difficult. Here, Xia et al. create a multi-layer memristor neural network with in-situ machine learning and achieve competitive image classification accuracy on a standard dataset.

Saved in:
Bibliographic Details
Main Authors: Can Li, Daniel Belkin, Yunning Li, Peng Yan, Miao Hu, Ning Ge, Hao Jiang, Eric Montgomery, Peng Lin, Zhongrui Wang, Wenhao Song, John Paul Strachan, Mark Barnell, Qing Wu, R. Stanley Williams, J. Joshua Yang, Qiangfei Xia
Format: article
Language:EN
Published: Nature Portfolio 2018
Subjects:
Science
Q
Online Access:https://doaj.org/article/b4e8c66198ed41eea8aa429291ec599c
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doaj.org/article/b4e8c66198ed41eea8aa429291ec599c

Similar Items