Memristive Model for Synaptic Circuits

被引：165
|
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
收藏
页码：767 / 771
页数：5
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