用于人工智能的可重新配置基酸电子产品
Hai-Tian Zhang1, Tae Joon Park1, A N M Nafiul Islam2
1School of Materials Engineering, Purdue University, West Lafayette, IN 47907, USA.
Science (New York, N.Y.)
|February 3, 2022
概括
研究人员使用矿材料创建了可重构的人工神经元和突触. 这些受大脑启发的计算组件可以根据需求进行编程,
科学领域:
- 材料科学
- 神经科学
- 计算机科学
背景情况:
- 可重新配置的设备允许按需编程电子电路.
- 矿尼基酸盐表现出对离子分布敏感的电子特性.
- 人工神经元和突触是脑启发计算的关键组成部分.
研究的目的:
- 在矿 NdNiO3 装置中展示按需创建人工神经元,突触和记忆电容.
- 调查这些可重新配置组件在储库计算和增量学习中的使用.
- 通过按需制造计算构件,探索适应性网络的新方向.
主要方法:
- 使用过制造的矿 NdNiO3 装置.
- 使用单射电脉冲来重新配置设备.
- 集成的实验数据与水库计算模拟.
- 模拟动态和静态网络用于增量学习任务.
主要成果:
- 我们成功地创造了可重构的人工神经元,突触和记忆电容.
- 在数字识别和心电图心跳分类中使用存储器电容器表现出卓越的性能.
- 在使用可重新配置的神经元和突触的增量学习场景中展示了动态网络的优越性能.
结论:
- 矿 NdNiO3 设备的按需重新配置使得创建基本的脑启发计算组件成为可能.
- 这些可重新配置的组件有望在储存器计算和自适应学习中的高级应用.
- 根据需求制造人工神经元和突触的能力为开发适应性和智能系统开辟了新的途径.
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