基于分门晶体管的神经元电路,具有非易失性记忆,用于生物神经元的恒温功能
Hansol Kim1, Sung Yun Woo1, Hyungjin Kim2
1School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Republic of Korea.
Biomimetics (Basel, Switzerland)
|June 26, 2024
概括
这项研究介绍了一种用于神经元电路的新型分门场效应晶体管 (S-G FET). 调整 S-G FET 的情况
科学领域:
- 神经形态工程的神经形态工程
- 固态设备 固态设备
- 人工智能的人工智能
背景情况:
- 生物神经元表现出恒常功能,这对于神经网络的稳定性至关重要.
- 现有的人工神经元电路在模仿这种恒常态行为方面面临挑战.
- 分隔门场效应晶体管 (S-G FET) 为人工神经元实现提供了潜力.
研究的目的:
- 为神经元电路提出和评估一种具有充电陷层的新型S-G FET.
- 为了证明控制神经元发射率调节的门电压 (Vth) 的能力.
- 在模拟的尖端神经网络 (SNN) 中验证性能提升.
主要方法:
- 采用化 (Si3N4) 充电陷层的S-G FET的制造.
- 使用翅膀结构将读取和Vth控制门分开,以防止介电降解.
- 开发一种脉冲调制电路,用于产生Program/Erase脉冲.
- 模拟使用开发的S-G FET进行在线无监督学习和分类的双层SNN.
主要成果:
- 通过调整Si3N4层中被困的电荷,成功调节了S-G FET的Vth.
- 通过增加神经元电路的Vth来降低高发射率.
- 在模拟的SNN中,识别率显著提高了8%.
结论:
- 拟议的S-G FET有效地模仿了生物神经元的恒常功能.
- 该设备可以精确控制神经元发射率,提高SNN的性能.
- 这种方法为开发更有效,更准确的神经形态系统提供了有希望的途径.
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