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Cited 62 time in webofscience Cited 61 time in scopus
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Artificial synaptic characteristics of TiO2/HfO2 memristor with self-rectifying switching for brain-inspired computing

Authors
Ryu, Ji-HoKim, Sungjun
Issue Date
Nov-2020
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
Neuromorphic; Memristor; Neural network; Resistive switching
Citation
CHAOS SOLITONS & FRACTALS, v.140
Indexed
SCIE
SCOPUS
Journal Title
CHAOS SOLITONS & FRACTALS
Volume
140
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/5972
DOI
10.1016/j.chaos.2020.110236
ISSN
0960-0779
1873-2887
Abstract
In this work, a built-in selector synaptic memristor is proposed to minimize sneak current in synapse array. The Ti/TiO2/HfO2/Si device exhibits nonlinear and high rectifying current-voltage characteristics compared to Ti/TiO2/Si device. Under negative bias conditions, the physical model supported by material analysis reveals that the Schottky barrier at the interface between Ti and TiO2 suppresses the current. Due to nonlinear and self-rectifying characteristics, a bilayer device has a significantly larger array size (> 10(5) x 10(5) ) with a securing read margin of 10%, using the modified half-bias scheme. A multi-level interface-type switching behavior is desired to implement synaptic functions, including potentiation and depression, and spike-timing-dependent plasticity. It was verified that the recognition rate in the bilayer device is significantly more accurate in a neural network model employing the Fashion MNIST dataset. (c) 2020 Elsevier Ltd. All rights reserved.
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