Skeleton-supported stochastic networks of organic memristive devices: Adaptations and learning

dc.contributor.author	Erokhina S.
dc.contributor.author	Sorokin V.
dc.contributor.author	Erokhin V.
dc.date.accessioned	2018-09-18T20:36:43Z
dc.date.available	2018-09-18T20:36:43Z
dc.date.issued	2015
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/141678
dc.description.abstract	© 2015 Author(s). Stochastic networks of memristive devices were fabricated using a sponge as a skeleton material. Cyclic voltage-current characteristics, measured on the network, revealed properties, similar to the organic memristive device with deterministic architecture. Application of the external training resulted in the adaptation of the network electrical properties. The system revealed an improved stability with respect to the networks, composed from polymer fibers.
dc.title	Skeleton-supported stochastic networks of organic memristive devices: Adaptations and learning
dc.type	Article
dc.relation.ispartofseries-issue	2
dc.relation.ispartofseries-volume	5
dc.collection	Публикации сотрудников КФУ
dc.source.id	SCOPUS-2015-5-2-SID84923349531

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Публикации сотрудников КФУ Scopus [24551]
Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.