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

Articolo
Data di Pubblicazione:
2015
Abstract:
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. (C) 2015 Author(s).
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Memristor; Statistical Networks; Self-Assembled; Adaptive
Elenco autori:
Erokhin, Victor
Autori di Ateneo:
EROKHIN VICTOR
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/335546
Pubblicato in:
AIP ADVANCES
Journal
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URL

https://aip.scitation.org/doi/10.1063/1.4913374
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