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

Faisal Bashir; Furqan Zahoor; Ali S. Alzahrani; Abdul Raouf Khan

doi:10.1109/TCSII.2023.3286810

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

Faisal Bashir^*
, Furqan Zahoor^*
, Ali S. Alzahrani
, Abdul Raouf Khan

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

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 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.

Original language	English
Pages (from-to)	4018-4022
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems II: Express Briefs
Volume	70
Issue number	11
DOIs	https://doi.org/10.1109/TCSII.2023.3286810
State	Published - 1 Nov 2023
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2004-2012 IEEE.

Keywords

LIF
Leaky integrate and fire
SB-MOSFET
SNN
neuromorphic computing

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/TCSII.2023.3286810

Cite this

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title = "A Single Schottky Barrier MOSFET-Based Leaky Integrate and Fire Neuron for Neuromorphic Computing",

abstract = "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 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.",

keywords = "LIF, Leaky integrate and fire, SB-MOSFET, SNN, neuromorphic computing",

author = "Faisal Bashir and Furqan Zahoor and Alzahrani, \{Ali S.\} and Khan, \{Abdul Raouf\}",

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AU - Zahoor, Furqan

AU - Alzahrani, Ali S.

AU - Khan, Abdul Raouf

PY - 2023/11/1

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N2 - 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 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.

AB - 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 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.

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

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this