Cited by 1,041Advanced Memory and Neural ComputingNeural Networks and ApplicationsNeural Networks and Reservoir Computing

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Experimental demonstration of associative memory with memristive neural networks

Pershin, Yuriy V., Di Ventra, Massimiliano·2010·Neural Networks

DOI 10.1016/j.neunet.2010.05.001

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Abstract

Synapses are essential elements for computation and information storage in both real and artificial neural systems. An artificial synapse needs to remember its past dynamical history, store a continuous set of states, and be "plastic" according to the pre-synaptic and post-synaptic neuronal activity. Here we show that all this can be accomplished by a memory-resistor (memristor for short). In particular, by using simple and inexpensive off-the-shelf components we have built a memristor emulator which realizes all required synaptic properties. Most importantly, we have demonstrated experimentally the formation of associative memory in a simple neural network consisting of three electronic neurons connected by two memristor-emulator synapses. This experimental demonstration opens up new possibilities in the understanding of neural processes using memory devices, an important step forward to reproduce complex learning, adaptive and spontaneous behavior with electronic neural networks.

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Authors: Pershin, Y. V., & Di Ventra, M.
Affiliations: University of South Carolina (US)
Corresponding author: Pershin, Yuriy V.
ORCID: Pershin, Yuriy V.
Venue: Neural Networks
Publisher: Elsevier BV
Published: 2010-09
Volume: 23
Issue: 7
Pages: 881-886
ISSN: 0893-6080 (ISSN-L)
DOI: 10.1016/j.neunet.2010.05.001
OpenAlex: W2015088745
Cited by: 1,041
References: 44
Citations by year: 2026: 26 · 2025: 38 · 2024: 51 · 2023: 53 · 2022: 68 · 2021: 73 · 2020: 84 · 2019: 85 · 2018: 99 · 2017: 61 · 2016: 76 · 2015: 64 · 2014: 93 · 2013: 66 · 2012: 56
FWCI: 42.28
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Neural Networks (publishedVersion)
PubMed (publishedVersion)
Funders: National Science Foundation
Topics: Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Reservoir Computing
Keywords: memristors, associative memory, memristive neural networks, artificial synapses, synaptic plasticity, electronic neurons, neuromorphic hardware
MeSH terms: Artificial Intelligence, Association Learning, Models, Neurological, Nerve Net, Neuronal Plasticity, Neurons, Synapses, Neural Networks, Computer

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Experimental demonstration of associative memory with memristive neural networks

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