Charge-based Neuromorphic Cell by InGaZnO Transistor and Implementation of Simple Scheme Spike-Timing-Dependent Plasticity

被引:0
|
作者
Tanaka, Chika [1 ]
Ikeda, Keiji [1 ]
机构
[1] Toshiba Memory Corp, Future Memory Dev Dept, Device Technol Res & Dev Ctr, Saiwai Ku, 1 Komukai Toshiba Cho, Kawasaki, Kanagawa 2128582, Japan
来源
2018 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2018年
关键词
Neuromorphic circuit; InGaZnO; Spiking neural network; Spike-timing-dependent plasticity; SYNAPSE;
D O I
10.1109/ISCAS.2018.8350932
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
This paper presents a novel charge-based neuromorphic cell architecture composed of 1-capacitor and 1-transistor using extremely low off leakage (<10(-21)A/mu m) oxide-semiconductor transistors. Thanks to ultra-long retention characteristics, circuit implementation of spike-timing-dependent plasticity, for spiking neural network, were successfully demonstrated. Cell array architecture and it operation were confirmed by simulation with charging and discharging control. Asynchronous STDP implementation was also achieved without complicated forming of input pulse, and low-power operation less than similar to 0.1pJ can be expected.
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页数:5
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