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Cellular neural networks with memristive cell devices

Cellular neural networks with memristive cell devices
Cellular neural networks with memristive cell devices
In this paper, we present simulation measurements of a memristor crossbar device. We designed a PCB memristor package and the appropriate measurement board. Technical details of these circuits are presented. Cellular like topology of this crossbar device can provide high density and local connectivity. We gave a formula to evaluate the direction of the change of the states of the memristor array in case of a given voltage input. Our simulation results show that a memristor crossbar can be a trainable weight-matrix of a fully connected neural network if the memristors have ohmic non-linearity.
cellular neural networks, memristor
938-941
Cserey, G.
f1aaa8f1-f6ef-4b48-b275-1d62316bec41
Rak, A.
4bc92a67-a11e-46d8-8b3c-b2c9fbca4708
Jakli, B.
0472a238-1152-4c4c-a905-87e11bdbadc2
Prodromakis, T.
d58c9c10-9d25-4d22-b155-06c8437acfbf
Cserey, G.
f1aaa8f1-f6ef-4b48-b275-1d62316bec41
Rak, A.
4bc92a67-a11e-46d8-8b3c-b2c9fbca4708
Jakli, B.
0472a238-1152-4c4c-a905-87e11bdbadc2
Prodromakis, T.
d58c9c10-9d25-4d22-b155-06c8437acfbf

Cserey, G., Rak, A., Jakli, B. and Prodromakis, T. (2010) Cellular neural networks with memristive cell devices. 17th IEEE International Conference on Electronics, Circuits and Systems - (ICECS 2010). 12 - 15 Dec 2010. pp. 938-941 . (doi:10.1109/ICECS.2010.5724667).

Record type: Conference or Workshop Item (Other)

Abstract

In this paper, we present simulation measurements of a memristor crossbar device. We designed a PCB memristor package and the appropriate measurement board. Technical details of these circuits are presented. Cellular like topology of this crossbar device can provide high density and local connectivity. We gave a formula to evaluate the direction of the change of the states of the memristor array in case of a given voltage input. Our simulation results show that a memristor crossbar can be a trainable weight-matrix of a fully connected neural network if the memristors have ohmic non-linearity.

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More information

Published date: December 2010
Venue - Dates: 17th IEEE International Conference on Electronics, Circuits and Systems - (ICECS 2010), 2010-12-12 - 2010-12-15
Keywords: cellular neural networks, memristor
Organisations: Nanoelectronics and Nanotechnology

Identifiers

Local EPrints ID: 351570
URI: http://eprints.soton.ac.uk/id/eprint/351570
PURE UUID: 85aba3b5-265e-4e58-b5f3-e04e5cae9dfa
ORCID for T. Prodromakis: ORCID iD orcid.org/0000-0002-6267-6909

Catalogue record

Date deposited: 29 Apr 2013 10:25
Last modified: 14 Mar 2024 13:41

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Contributors

Author: G. Cserey
Author: A. Rak
Author: B. Jakli
Author: T. Prodromakis ORCID iD

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