记忆电阻器
可扩展性
记忆晶体管
计算机科学
电子线路
CMOS芯片
人工神经网络
电子工程
非易失性存储器
电压
计算机体系结构
电阻随机存取存储器
人工智能
电气工程
工程类
计算机硬件
数据库
作者
Yang Zhang,Xiaoping Wang,Yi Li,Eby G. Friedman
出处
期刊:IEEE Transactions on Circuits and Systems Ii-express Briefs
[Institute of Electrical and Electronics Engineers]
日期:2016-09-01
卷期号:64 (7): 767-771
被引量:153
标识
DOI:10.1109/tcsii.2016.2605069
摘要
As a promising alternative for next-generation memory, memristors provide several useful features such as high density, nonvolatility, low power, and good scalability as compared with conventional CMOS-based memories. In this brief, a voltage-controlled threshold memristive model is proposed, which is based on experimental data of memristive devices. Moreover, the model is more suitable for the design of memristor-based synaptic circuits as compared with other memristive models. The effects of memristance variations are considered in the proposed model to evaluate the behavior of memristive synapses within memristor-based neural networks.
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