可重新配置的级联热神经istor用于神经形态计算
Erbin Qiu1,2, Yuan-Hang Zhang2, Massimiliano Di Ventra2
1Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, 92093, USA.
Advanced materials (Deerfield Beach, Fla.)
|September 28, 2023
概括
研究人员探索了用于大脑启发的计算的热神经晶体. 这些设备使用二氧化瓦纳.
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:
- 互补金属氧化物半导体 (CMOS) 技术主导神经网络硬件.
- 需要替代方法来实现更节能和可扩展的计算.
研究的目的:
- 探索热神经元作为神经网络的新硬件实现.
- 用热相互作用来证明可重新配置的动态和信息处理.
主要方法:
- 利用二氧化瓦纳 (VO2) 中的绝缘体到金属转换 (IMT) 来创建热神经元.
- 通过实验性表征来证明设备的功能.
- 开发了一个理论模型来阐明潜在的物理机制.
主要成果:
- 通过使用热神经阻尼器模仿生物神经元,实现了多样化的电动力学.
- 在单个氧化物装置内证明了抑制功能.
- 实现的级联信息流仅通过热相互作用来实现.
结论:
- 确立了热神经元作为脑启发计算的可行组件.
- 奠定了可扩展和节能热神经网络的基础.
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