Published February 2015 | Version v1
Journal article Metadata-only

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

Creators

  • 1. IFMB, Kazan Federal University, Kremliovskaya str. 18, 420008, Kazan (Russian Federation)
  • 2. CNR-IMEM, Parco delle Scienze 37/A, 43124, Parma Italy (Italy)

Description

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

Additional details

Identifiers

DOI
10.1063/1.4913374;

Publishing Information

Journal Title
AIP Advances
Journal Volume
5
Journal Issue
2
Journal Page Range
p. 027129-027129.6
ISSN
2158-3226
CODEN
AAIDBI

INIS

Country of Publication
United States
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
47024000
Subject category
S36: MATERIALS SCIENCE;
Descriptors DEI
ELECTRIC POTENTIAL; ELECTRICAL PROPERTIES; EQUIPMENT; FIBERS; POLYMERS; SKELETON; STABILITY; STOCHASTIC PROCESSES
Descriptors DEC
BODY; ORGANS; PHYSICAL PROPERTIES

Optional Information

Notes
(c) 2015 Author(s)