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基于ZnO忆阻器的神经突触仿生电子器件
Authors
张洪亮
曹鸿涛
+8 more
李俊
李康
梁凌燕
潘若冰
竺立强
胡丽娟
诸葛飞
高俊华
Publication date
1 January 2017
Publisher
Abstract
本文采用ZnO忆阻器模拟了生物神经突触的记忆和学习功能。ZnO突触器件表现出典型的随时间指数衰减的突触后兴奋电流(EPSC),以及EPSC的双脉冲增强行为。在此基础上,实现了学习-遗忘-再学习的经验式学习行为,以及四种不同种类的电脉冲时刻依赖可塑性学习规则。ZnO突触器件实现了超低能耗操作,单次突触行为能耗最低为1.6pJ,表明其可以用来构筑未来的人工神经网络硬件系统,最终开发出与人脑结构类似的认知型计算机以及类人机器人
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Last time updated on 22/01/2018