Avalanches and edge-of-chaos learning in neuromorphic nanowire networks

Neuromorphic nanowire networks are found to exhibit neural-like dynamics, including phase transitions and avalanche criticality. Hochstetter and Kuncic et al. show that the dynamical state at the edge-of-chaos is optimal for learning and favours computationally complex information processing tasks.

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Autores principales:	Joel Hochstetter, Ruomin Zhu, Alon Loeffler, Adrian Diaz-Alvarez, Tomonobu Nakayama, Zdenka Kuncic
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/f1e7ff5dc9f5497497fbb5eca62674e4
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spelling	oai:doaj.org-article:f1e7ff5dc9f5497497fbb5eca62674e42021-12-02T16:10:51ZAvalanches and edge-of-chaos learning in neuromorphic nanowire networks10.1038/s41467-021-24260-z2041-1723https://doaj.org/article/f1e7ff5dc9f5497497fbb5eca62674e42021-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-24260-zhttps://doaj.org/toc/2041-1723Neuromorphic nanowire networks are found to exhibit neural-like dynamics, including phase transitions and avalanche criticality. Hochstetter and Kuncic et al. show that the dynamical state at the edge-of-chaos is optimal for learning and favours computationally complex information processing tasks.Joel HochstetterRuomin ZhuAlon LoefflerAdrian Diaz-AlvarezTomonobu NakayamaZdenka KuncicNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Joel Hochstetter Ruomin Zhu Alon Loeffler Adrian Diaz-Alvarez Tomonobu Nakayama Zdenka Kuncic Avalanches and edge-of-chaos learning in neuromorphic nanowire networks
description	Neuromorphic nanowire networks are found to exhibit neural-like dynamics, including phase transitions and avalanche criticality. Hochstetter and Kuncic et al. show that the dynamical state at the edge-of-chaos is optimal for learning and favours computationally complex information processing tasks.
format	article
author	Joel Hochstetter Ruomin Zhu Alon Loeffler Adrian Diaz-Alvarez Tomonobu Nakayama Zdenka Kuncic
author_facet	Joel Hochstetter Ruomin Zhu Alon Loeffler Adrian Diaz-Alvarez Tomonobu Nakayama Zdenka Kuncic
author_sort	Joel Hochstetter
title	Avalanches and edge-of-chaos learning in neuromorphic nanowire networks
title_short	Avalanches and edge-of-chaos learning in neuromorphic nanowire networks
title_full	Avalanches and edge-of-chaos learning in neuromorphic nanowire networks
title_fullStr	Avalanches and edge-of-chaos learning in neuromorphic nanowire networks
title_full_unstemmed	Avalanches and edge-of-chaos learning in neuromorphic nanowire networks
title_sort	avalanches and edge-of-chaos learning in neuromorphic nanowire networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/f1e7ff5dc9f5497497fbb5eca62674e4
work_keys_str_mv	AT joelhochstetter avalanchesandedgeofchaoslearninginneuromorphicnanowirenetworks AT ruominzhu avalanchesandedgeofchaoslearninginneuromorphicnanowirenetworks AT alonloeffler avalanchesandedgeofchaoslearninginneuromorphicnanowirenetworks AT adriandiazalvarez avalanchesandedgeofchaoslearninginneuromorphicnanowirenetworks AT tomonobunakayama avalanchesandedgeofchaoslearninginneuromorphicnanowirenetworks AT zdenkakuncic avalanchesandedgeofchaoslearninginneuromorphicnanowirenetworks
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Avalanches and edge-of-chaos learning in neuromorphic nanowire networks

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