A Single Schottky Barrier MOSFET-Based Leaky Integrate and Fire Neuron for Neuromorphic Computing

被引：5
|
作者：
Bashir, Faisal [1 ]
Zahoor, Furqan [2 ]
Alzahrani, Ali S. [1 ]
Khan, Abdul Raouf [3 ]
机构：
[1] King Faisal Univ, Coll Comp Sci & Informat Technol, Dept Comp Engn, Al Hasa 31982, Saudi Arabia
[2] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore, Singapore
[3] King Faisal Univ, Dept Comp Sci, Al Hasa 31982, Saudi Arabia
来源：
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2023年 / 70卷 / 11期
关键词：
Leaky integrate and fire; SB-MOSFET; SNN; LIF; neuromorphic computing;
D O I：
10.1109/TCSII.2023.3286810
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：
In this brief, a Schottky Barrier MOSFET (SB-MOSFET) based on Impact Ionization mechanism is used to design a leaky integrate and fire (LIF) neuron with considerable enhancement in area, energy and cost is proposed. Using 2D calibrated simulation, we confirmed that SB-MOSFET LIF is able to replicate the neuron behavior precisely without using external circuitry. The proposed LIF neuron shows significantly lower energy per spike of similar to 4 pJ/spike, which is lowest among the single transistor based neurons present in the literature. The recognition precision of 89.2% has been accomplished for Modified National Institute of Standards and Technology (MNIST) image. Besides this, SB-MOSFET doesn't require any doped regions, therefore it can be fabricated with low thermal budget.
引用
收藏
页码：4018 / 4022
页数：5
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