Area-efficient memristor spiking neural networks and supervised learning method

被引：0

作者：

Errui ZHOU ^{[1
]}

Liang FANG ^{[1
]}

Rulin LIU ^{[1
]}

Zhensen TANG ^{[1
]}

机构：

[1] Institute for Quantum Information & State Key Laboratory of High Performance Computing, College of Computer,National University of Defense Technology

来源：

Science China(Information Sciences) | 2019年 / 62卷 / 09期

基金：

中国国家自然科学基金;

关键词：

simulation; Area-efficient memristor spiking neural networks and supervised learning method;

D O I：

暂无

中图分类号：

TN60 [一般性问题]; TP18 [人工智能理论];

学科分类号：

080903 ; 081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Dear editor,Memristors have attracted a lot of attention since HP Labs first reported their memristive devices [1].They have been employed in many fields, including non-volatile memory, image processing, and neuromorphic computing [2–4]. In neuromorphic computing, memristors are usually used as synapses because they can store synaptic weights by their conductance [4]. Most memristors have the struc-

引用

页码：196 / 198

页数：3

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