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-  2018 

基于忆阻器的脉冲神经网络研究综述

DOI: doi:10.7507/1001-5515.201703091

Keywords: 人工智能, 脉冲神经网络, 忆阻器, 脉冲时间依赖可塑性机制

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Abstract:

人工智能的快速发展对计算神经科学的计算速度、资源消耗和生物解释性提出了更高的要求。脉冲神经网络能够携带大量信息,实现对大脑信息处理方式的模仿。它的硬件化是实现其强大计算能力的重要途径,但也是极具挑战性的技术难题。忆阻器是目前功能最接近神经元突触的电子器件,能够以与生物大脑高度相似的脉冲时间依赖可塑性(STDP)机制响应脉冲电压,成为近几年研究构建脉冲神经网络硬件电路的热点。本文通过查阅国内外相关文献,对近几年基于忆阻器的脉冲神经网络的研究工作进行了深入了解和介绍

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