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

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.
Authors:
;  [1] ;  [1] ;  [2]
  1. IFMB, Kazan Federal University, Kremliovskaya str. 18, 420008, Kazan (Russian Federation)
  2. (Italy)
Publication Date:
OSTI Identifier:
22454458
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Advances; Journal Volume: 5; Journal Issue: 2; Other Information: (c) 2015 Author(s); Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; ELECTRIC POTENTIAL; ELECTRICAL PROPERTIES; EQUIPMENT; FIBERS; POLYMERS; SKELETON; STABILITY; STOCHASTIC PROCESSES