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Linking Conductive Filament Properties and Evolution to Synaptic Behavior of RRAM Devices for Neuromorphic Applications

机译:将导电丝的特性和演化与RRAM设备在神经形态应用中的突触行为联系起来

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摘要

We perform a comparative study of HfO and TaO resistive switching memory (RRAM) devices for their possible application as electronic synapses. By means of electrical characterization and simulations, we link their electrical behavior (digital or analog switching) to the properties and evolution of the conductive filament (CF). More specifically, we identify that bias-polarity-dependent digital switching in HfO RRAM is primarily related to the creation and rupture of an oxide barrier. Conversely, the modulation of the CF size in TaO RRAM allows bias-polarity-independent analog switching with multiple states. Therefore, when the TaO RRAM is used to implement a synapse in multilayer perceptron neural networks operated by back-propagation algorithms, patterns in handwritten digits can be recognized with high accuracy.
机译:我们对HfO和TaO电阻开关存储器(RRAM)器件作为电子突触的可能应用进行了比较研究。通过电特性描述和仿真,我们将其电行为(数字或模拟开关)与导电灯丝(CF)的特性和演变联系起来。更具体地说,我们确定HfO RRAM中依赖于偏置极性的数字开关主要与氧化物势垒的产生和破裂有关。相反,TaO RRAM中CF大小的调制允许具有多种状态的偏置极性独立的模拟开关。因此,当使用TaO RRAM在通过反向传播算法操作的多层感知器神经网络中实现突触时,可以以高精度识别手写数字中的模式。

著录项

  • 来源
    《IEEE Electron Device Letters》 |2017年第9期|1220-1223|共4页
  • 作者单位

    Department of Materials Science and Engineering, Pohang University of Science and Technology, Pohang, South Korea;

    MDLab s.r.l., Reggio Emilia, Italy;

    Department of Materials Science and Engineering, Pohang University of Science and Technology, Pohang, South Korea;

    Department of Materials Science and Engineering, Pohang University of Science and Technology, Pohang, South Korea;

    Dipartimento di Scienze e Metodi dell’Ingegneria, Università degli Studi di Modena e Reggio Emilia, Reggio Emilia, Italy;

    Department of Materials Science and Engineering, Pohang University of Science and Technology, Pohang, South Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hafnium compounds; Switches; Pattern recognition; Neuromorphics; Modulation; Biological neural networks; Neurons;

    机译:compounds化合物开关模式识别神经形态调制生物神经网络神经元;

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