Novel hardware and concepts for unconventional computing

Abstract Neuromorphic systems are currently experiencing a rapid upswing due to the fact that today's CMOS (complementary metal oxide silicon) based technologies are increasingly approaching their limits. In particular, for the area of machine learning, energy consumption of today's electr...

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Autor principal:	Martin Ziegler
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/11fcfe0dbd154c3c9ecbdf59720bcfbc
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spelling	oai:doaj.org-article:11fcfe0dbd154c3c9ecbdf59720bcfbc2021-12-02T15:33:11ZNovel hardware and concepts for unconventional computing10.1038/s41598-020-68834-12045-2322https://doaj.org/article/11fcfe0dbd154c3c9ecbdf59720bcfbc2020-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-68834-1https://doaj.org/toc/2045-2322Abstract Neuromorphic systems are currently experiencing a rapid upswing due to the fact that today's CMOS (complementary metal oxide silicon) based technologies are increasingly approaching their limits. In particular, for the area of machine learning, energy consumption of today's electronics is an important limitation, that also contributes toward the ever-increasing impact of digitalization on our climate. Thus, in order to better meet the special requirements of unconventional computing, new physical substrates for bio-inspired computing schemes are extensively exploited. The aim of this Guest Edited Collection is to provide a platform for interdisciplinary research along three main lines: memristive materials and devices, emulation of cellular learning (neurons and synapses), and unconventional computing and network schemes.Martin ZieglerNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-3 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Martin Ziegler Novel hardware and concepts for unconventional computing
description	Abstract Neuromorphic systems are currently experiencing a rapid upswing due to the fact that today's CMOS (complementary metal oxide silicon) based technologies are increasingly approaching their limits. In particular, for the area of machine learning, energy consumption of today's electronics is an important limitation, that also contributes toward the ever-increasing impact of digitalization on our climate. Thus, in order to better meet the special requirements of unconventional computing, new physical substrates for bio-inspired computing schemes are extensively exploited. The aim of this Guest Edited Collection is to provide a platform for interdisciplinary research along three main lines: memristive materials and devices, emulation of cellular learning (neurons and synapses), and unconventional computing and network schemes.
format	article
author	Martin Ziegler
author_facet	Martin Ziegler
author_sort	Martin Ziegler
title	Novel hardware and concepts for unconventional computing
title_short	Novel hardware and concepts for unconventional computing
title_full	Novel hardware and concepts for unconventional computing
title_fullStr	Novel hardware and concepts for unconventional computing
title_full_unstemmed	Novel hardware and concepts for unconventional computing
title_sort	novel hardware and concepts for unconventional computing
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/11fcfe0dbd154c3c9ecbdf59720bcfbc
work_keys_str_mv	AT martinziegler novelhardwareandconceptsforunconventionalcomputing
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Novel hardware and concepts for unconventional computing

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