An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation

Recurrent spiking neural networks have garnered interest due to their energy efficiency; however, they suffer from lower accuracy compared to conventional neural networks. Here, the authors present an alternative neuron model and its efficient hardware implementation, demonstrating high classificati...

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Autores principales:	Ahmed Shaban, Sai Sukruth Bezugam, Manan Suri
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/b9e65d38422b411399499f0831f7338c
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spelling	oai:doaj.org-article:b9e65d38422b411399499f0831f7338c2021-12-02T15:23:18ZAn adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation10.1038/s41467-021-24427-82041-1723https://doaj.org/article/b9e65d38422b411399499f0831f7338c2021-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-24427-8https://doaj.org/toc/2041-1723Recurrent spiking neural networks have garnered interest due to their energy efficiency; however, they suffer from lower accuracy compared to conventional neural networks. Here, the authors present an alternative neuron model and its efficient hardware implementation, demonstrating high classification accuracy across a range of datasets.Ahmed ShabanSai Sukruth BezugamManan SuriNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Ahmed Shaban Sai Sukruth Bezugam Manan Suri An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation
description	Recurrent spiking neural networks have garnered interest due to their energy efficiency; however, they suffer from lower accuracy compared to conventional neural networks. Here, the authors present an alternative neuron model and its efficient hardware implementation, demonstrating high classification accuracy across a range of datasets.
format	article
author	Ahmed Shaban Sai Sukruth Bezugam Manan Suri
author_facet	Ahmed Shaban Sai Sukruth Bezugam Manan Suri
author_sort	Ahmed Shaban
title	An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation
title_short	An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation
title_full	An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation
title_fullStr	An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation
title_full_unstemmed	An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation
title_sort	adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b9e65d38422b411399499f0831f7338c
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An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation

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