高调节的突触调制在照片激活的远程充电陷内存中,用于基于硬件的容错学习
Je-Jun Lee1,2, Hojin Choi1, Ju-Hee Lee1
1Department of Electrical and Computer Engineering, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea.
Advanced materials (Deerfield Beach, Fla.)
|October 3, 2025
概括
研究人员为人工突触开发了一种容错的学习算法,以提高深度学习的效率. 这项创新降低了能源消耗,并提高了带有噪音标签的数据集的识别准确性,最大限度地减少了数据准备需求.
科学领域:
- 人工智能的人工智能
- 计算机工程 计算机工程
- 材料科学 材料科学 材料科学
背景情况:
- 深度学习的增长增加了能源需求,主要来自推断过程中的矩阵向量运算.
- 内存计算提供了效率,但在现实数据中与复杂的算法和杂的标签扎.
- 由于数据注释中的错误 (噪音标签),当前系统面临识别效率低下的问题.
研究的目的:
- 提出一个基于硬件的,对可调节操作的人工突触的容错学习算法.
- 为了能够选择性地减弱因误导信号引起的重量更新.
- 提高在内存计算系统中的训练效率和识别准确度,这些系统具有噪音数据集.
主要方法:
- 开发了一个可调节的人工突触的容错学习算法.
- 集成学习和监管信号用于选择性重量更新控制.
- 使用照片激活的远程充电陷存储器设备,具有缺陷工程六角化 (h-BN).
主要成果:
- 在基于h-BN的设备中达到4380的高突触可调度比.
- 该系统有效地抑制了来自错误标记的数据的重量更新信号.
- 在被错误标记的修改国家标准与技术研究所 (MNIST) 数据集上证明了更好的识别准确性.
结论:
- 可调节的突触设备可以提高噪音标签的数据集的内存计算效率.
- 拟议的算法减少了对大量数据清理和准备的需求.
- 这种方法为更节能和更强大的深度学习系统提供了一条途径.
关键词:
充电陷的记忆陷是一个充电陷.错误耐受性学习的学习光电子突触 (optoelectronic synapse) 是一种可视电子突触 (optoelectronic synapse) 是一种可视电子突触 (optoelectronic synapse) 是一种可视电子突触 (optoelectronic synapse) 是一种可视电子突触 (optoelectronic synapse).用照片诱导的兴奋剂.远程充电传输兴奋剂的使用.更多相关视频
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