人工神经元模块中的尖端频率适应性和多重量协同作用通过双功能NbO记忆器
Shuai-Ming Chen1, Li-Chung Shih1, Jing-Ci Gao1
1Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan. jenschen@ncku.edu.tw.
Nanoscale horizons
|July 4, 2025
概括
基于氧化 (NbOx) 的双功能记忆器使先进的人工神经元能够进行神经形态计算. 这些设备作为值交换记忆器或动态记忆器,促进复杂的尖端神经网络功能.
科学领域:
- 材料科学 材料科学 材料科学
- 神经科学是一个神经科学.
- 计算机工程 计算机工程
背景情况:
- 目前的人工神经元在神经形态硬件方面面临局限性.
- 双功能记忆器为高级神经功能提供了一个有前途的解决方案.
研究的目的:
- 制造基于NbO的双功能记忆器,用于构建人工神经元.
- 探索这些memristors在构建振荡单元和神经元模块中用于神经网络的应用.
主要方法:
- 基于NbOx的双功能记忆器的制造.
- 作为基于电压成型的值切换记忆器 (TSM) 或动态记忆器 (DyM) 操作.
- 对振荡单元和加权神经元模块的TSM的实施.
- 利用DYM进行序列编码和短期可塑性.
主要成果:
- 使用基于TSM的模块证明了实时的输入峰值的时空总和.
- 实现了尖峰总和和多重量协同作用.
- 成功实现了一个使用DyMs进行时间顺序识别的序列编码器.
- 发育了强化和衰减神经元,具有短期尖端频率适应.
结论:
- NbO双功能记忆器为人工神经元提供了多样化的尖端性能.
- 这些设备为下一代生物启发的尖端神经网络提供了基础.
- 开发的模块在神经形态硬件中实现了先进的计算能力.
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