Memristive Model for Synaptic Circuits

被引：167

作者：

Zhang, Yang ^{[1
]}

Wang, Xiaoping ^{[1
]}

Li, Yi ^{[2
,3
]}

Friedman, Eby G. ^{[4
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Peoples R China

[2] Huazhong Univ Sci & Technol, Sch Opt & Elect Informat, Wuhan 430074, Peoples R China

[3] Huazhong Univ Sci & Technol, WNLO, Wuhan 430074, Peoples R China

[4] Univ Rochester, Dept Elect & Comp Engn, 601 Elmwood Ave, Rochester, NY 14627 USA

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2017年 / 64卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Crossbar array; memristor; neural network; synaptic circuits; threshold model; SPICE MODEL; SYSTEM; DESIGN;

D O I：

10.1109/TCSII.2016.2605069

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

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.

引用

页码：767 / 771

页数：5

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