接触工程氧化物记忆电晶体管用于基于恒温的高线性和精确的神经形态计算.
San Nam1, Donghyun Kang1, Seong-Pil Jeon2
1School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
Small (Weinheim an der Bergstrasse, Germany)
|January 6, 2025
概括
三端氧化物晶体管可以在神经形态计算中实现平衡. 这项技术通过模仿生物神经网络平衡,为人工智能应用提供高度线性突触重量更新和更高的准确性.
科学领域:
- 神经形态工程的神经形态工程
- 材料科学 材料科学 材料科学
- 人工智能的人工智能
背景情况:
- 恒温对于生物神经网络至关重要,平衡神经元活动以获得最佳的信息处理和学习.
- 传统的双终端记忆器缺乏全球调节,这限制了它们在神经形态系统中实现平静功能的能力.
研究的目的:
- 为了证明基于三端氧化物memtransistor的恒常态突触用于神经形态计算.
- 为了实现高度线性突触重量更新和提高准确性,使用门控制的--氧化 (IGZO) memtransistors.
主要方法:
- 接触式工程--氧化 (IGZO) 晶体管的开发,采用优化的源/排水电极和接口层.
- 利用杆门控制来进行突触重量缩放,使神经形态计算具有高线性和精度.
- 通过突触缩放和状门电压控制对潜在的更高阶突触功能的恒温的模拟.
主要成果:
- 实现了具有高电流切换比率 (> 10 ^ 4) 和可靠耐久性的 memtransistors.
- 证明了高度线性突触重量更新,非线性值为0.01 (强化) 和-0.01 (抑郁).
- 在使用恒常态突触缩放的数字图像中,实现了91.77%的识别精度.
结论:
- 接触式设计的IGZO晶体管在神经形态计算中有效实现平衡.
- 开发的设备提供高线性,精度和效率,为先进的人工智能铺平了道路.
- 通过先进的门电压控制策略来模拟高阶突触功能的潜力.
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