Implementation of artificial neurons with tunable width via magnetic anisotropy

APPLIED PHYSICS LETTERS(2021)

引用 2|浏览21
暂无评分
摘要
We report an experimental implementation of width-tunable neurons to train a binary neural network. The angle-dependent magnetic behavior in an oxide thin film highly mimics neurons with width-controllable activation window, providing an opportunity to train the activation functions and weights toward binary values. We apply this feature to train the MNIST dataset using a 684-800-10 fully connected network and achieve a high accuracy of 97.4%, thus opening an implementation strategy toward training neural networks.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要