可调谐的柔性人工突触:通向可穿戴电子系统的新途径

作者:  时间:2018-09-23  热度:

   电气与电子工程

   #电子与自旋电子元件

   可调谐的柔性人工突触:通向可穿戴电子系统的新途径

   论文标题:Tunable flexible artificial synapses: a new path toward a wearable electronic system

   期刊:npj Flexible Electronics

   作者:Kunlong Yang et al

   发表时间: 2018/7/23

   数字识别码:10.1186/s41528-018-0033-1

   原文链接:https://www.nature.com/articles/s41528-018-0033-1?utm_source=Other_websiteutm_medium=Website_linksWebsite_linksutm_content=JesGuo-Nature-npj_Flexible_Electronics-Engineering_of_Electrical_and_Electronic-Chinautm_campaign=NPJ_USG_JRCN_JG_NPJ_Tunable

   人工突触:具有机械和突触灵活性的记忆晶体管

   基于记忆晶体管的机械柔性人工突触,可以表现出不同类型的突触可塑性。突触是神经形态计算的一个基本组成部分(一种大脑启发计算方法,旨在提供较传统方法而言更为高效的计算方法)。 目前,Yiqiang Zhan,Lirong Zheng和Fernando Seoane与来自瑞典和中国的合作者们,报道了一种人工突触,该突触是基于具有机械柔性的记忆晶体管设计的。 这种突触设计的关键是一个三端结构,它可以进行栅极调谐。 通过调节栅极端上的电压,使得器件的变化能够得到补偿,从而提高突触的一致性和可重复性。 研究人员还发现栅极调谐可以将每次峰值事件的总能量消耗降低至45 fJ,并展示了对于复制神经形态行为很重要的各种突触塑性特征。

   摘要

   柔性电子元件一直被认为是实现可穿戴电子系统的有效方法。然而,由于传统的计算模式无法与现有的柔性器件相匹配,导致该领域的发展停滞不前。本研究提出了一种可实现这一目标的新方法,即将柔性器件与神经形态架构结合在一起。通过精心设计和优化记忆晶体管,创建一种高性能的柔性人工突触。该器件性能好,可在515%动态范围内,实现在10,000个相同脉冲信号下,具有接近线性的非易失性电阻变化,并且每个脉冲的能量消耗低至45fJ。它还拥有多个突触可塑性特征,使其可用于实时的在线学习。此外,由于其三端结构的适应性,该器件的一致性和可重复性得到提高,同时还可降低能耗。 这项工作为未来的可穿戴计算提供了一个非常可行的解决方案。

  

   原理示意图和工作机理。 (a)一种生物突触和(b)人工突触的原理示意图。

   Abstract:

   The flexible electronics has been deemed to be a promising approach to the wearable electronic systems. However, the mismatching between the existing flexible deices and the conventional computing paradigm results an impasse in this field. In this work, a new way to access to this goal is proposed by combining flexible devices and the neuromorphic architecture together. To achieve that, a high-performance flexible artificial synapse is created based on a carefully designed and optimized memristive transistor. The device exhibits high-performance which has near-linear non-volatile resistance change under 10,000 identical pulse signals within the 515% dynamic range, and has the energy consumption as low as 45 fJ per pulse. It also displays multiple synaptic plasticity features, which demonstrates its potential for real-time online learning. Besides, the adaptability by virtue of its three-terminal structure specifically contributes its improved uniformity, repeatability, and reduced power consumption. This work offers a very viable solution for the future wearable computing.

   阅读论文原文,请访问

   https://www.nature.com/articles/s41528-018-0033-1?utm_source=Other_websiteutm_medium=Website_linksWebsite_linksutm_content=JesGuo-Nature-npj_Flexible_Electronics-Engineering_of_Electrical_and_Electronic-Chinautm_campaign=NPJ_USG_JRCN_JG_NPJ_Tunable

   (来源:科学网)

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