skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Organic memristive device as key element for neuromorphic networks

Abstract

Organic memristive device has three important properties allowing to consider it as a key element of neuromorphic systems. First, its electrical properties are somehow similar to those of synapses. Second, it can be easily transferred into an oscillator. Third, organic nature of the devices allow to assemble them into stochastic 3D networks capable to learning and adaptations.

Authors:
 [1]
  1. CNR-IMEM, Parco Area delle Scienze, 43124, Parma (Italy)
Publication Date:
OSTI Identifier:
22391072
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1648; Journal Issue: 1; Conference: ICNAAM-2014: International Conference on Numerical Analysis and Applied Mathematics 2014, Rhodes (Greece), 22-28 Sep 2014; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ELECTRICAL PROPERTIES; LEARNING; ORGANIC COMPOUNDS; OSCILLATORS; STOCHASTIC PROCESSES

Citation Formats

Erokhin, Victor. Organic memristive device as key element for neuromorphic networks. United States: N. p., 2015. Web. doi:10.1063/1.4912535.
Erokhin, Victor. Organic memristive device as key element for neuromorphic networks. United States. doi:10.1063/1.4912535.
Erokhin, Victor. Tue . "Organic memristive device as key element for neuromorphic networks". United States. doi:10.1063/1.4912535.
@article{osti_22391072,
title = {Organic memristive device as key element for neuromorphic networks},
author = {Erokhin, Victor},
abstractNote = {Organic memristive device has three important properties allowing to consider it as a key element of neuromorphic systems. First, its electrical properties are somehow similar to those of synapses. Second, it can be easily transferred into an oscillator. Third, organic nature of the devices allow to assemble them into stochastic 3D networks capable to learning and adaptations.},
doi = {10.1063/1.4912535},
journal = {AIP Conference Proceedings},
number = 1,
volume = 1648,
place = {United States},
year = {Tue Mar 10 00:00:00 EDT 2015},
month = {Tue Mar 10 00:00:00 EDT 2015}
}