Standard

Hardware elementary perceptron based on polyaniline memristive devices. / Demin, V. A.; Erokhin, V. V.; Emelyanov, A. V.; Battistoni, S.; Baldi, G.; Iannotta, S.; Kashkarov, P. K.; Kovalchuk, M. V.

In: Organic Electronics, Vol. 25, 3127, 14.06.2015, p. 16-20.

Research output: Contribution to journal › Article › peer-review

Harvard

Demin, VA, Erokhin, VV, Emelyanov, AV, Battistoni, S, Baldi, G, Iannotta, S, Kashkarov, PK & Kovalchuk, MV 2015, 'Hardware elementary perceptron based on polyaniline memristive devices', Organic Electronics, vol. 25, 3127, pp. 16-20. https://doi.org/10.1016/j.orgel.2015.06.015

APA

Demin, V. A., Erokhin, V. V., Emelyanov, A. V., Battistoni, S., Baldi, G., Iannotta, S., Kashkarov, P. K., & Kovalchuk, M. V. (2015). Hardware elementary perceptron based on polyaniline memristive devices. Organic Electronics, 25, 16-20. [3127]. https://doi.org/10.1016/j.orgel.2015.06.015

Vancouver

Demin VA, Erokhin VV, Emelyanov AV, Battistoni S, Baldi G, Iannotta S et al. Hardware elementary perceptron based on polyaniline memristive devices. Organic Electronics. 2015 Jun 14;25:16-20. 3127. https://doi.org/10.1016/j.orgel.2015.06.015

Author

Demin, V. A. ; Erokhin, V. V. ; Emelyanov, A. V. ; Battistoni, S. ; Baldi, G. ; Iannotta, S. ; Kashkarov, P. K. ; Kovalchuk, M. V. / Hardware elementary perceptron based on polyaniline memristive devices. In: Organic Electronics. 2015 ; Vol. 25. pp. 16-20.

BibTeX

@article{6c14754eb64e49e1a84d1a4835ae2835,
title = "Hardware elementary perceptron based on polyaniline memristive devices",
abstract = "Abstract Elementary perceptron is an artificial neural network with a single layer of adaptive links and one output neuron that can solve simple linearly separable tasks such as invariant pattern recognition, linear approximation, prediction and others. We report on the hardware realization of the elementary perceptron with the use of polyaniline-based memristive devices as the analog link weights. An error correction algorithm was used to get the perceptron to learn the implementation of the NAND and NOR logic functions as examples of linearly separable tasks. The physical realization of an elementary perceptron demonstrates the ability to form the hardware-based neuromorphic networks with the use of organic memristive devices. The results provide a great promise toward new approaches for very compact, low-volatile and high-performance neurochips that could be made for a huge number of intellectual products and applications.",
keywords = "Machine learning, Memristor, Neuromorphic computing, Pattern classification, Perceptron, Polyaniline",
author = "Demin, {V. A.} and Erokhin, {V. V.} and Emelyanov, {A. V.} and S. Battistoni and G. Baldi and S. Iannotta and Kashkarov, {P. K.} and Kovalchuk, {M. V.}",
note = "Publisher Copyright: {\textcopyright} 2015 Elsevier B.V.",
year = "2015",
month = jun,
day = "14",
doi = "10.1016/j.orgel.2015.06.015",
language = "English",
volume = "25",
pages = "16--20",
journal = "Organic Electronics",
issn = "1566-1199",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Hardware elementary perceptron based on polyaniline memristive devices

AU - Demin, V. A.

AU - Erokhin, V. V.

AU - Emelyanov, A. V.

AU - Battistoni, S.

AU - Baldi, G.

AU - Iannotta, S.

AU - Kashkarov, P. K.

AU - Kovalchuk, M. V.

N1 - Publisher Copyright: © 2015 Elsevier B.V.

PY - 2015/6/14

Y1 - 2015/6/14

N2 - Abstract Elementary perceptron is an artificial neural network with a single layer of adaptive links and one output neuron that can solve simple linearly separable tasks such as invariant pattern recognition, linear approximation, prediction and others. We report on the hardware realization of the elementary perceptron with the use of polyaniline-based memristive devices as the analog link weights. An error correction algorithm was used to get the perceptron to learn the implementation of the NAND and NOR logic functions as examples of linearly separable tasks. The physical realization of an elementary perceptron demonstrates the ability to form the hardware-based neuromorphic networks with the use of organic memristive devices. The results provide a great promise toward new approaches for very compact, low-volatile and high-performance neurochips that could be made for a huge number of intellectual products and applications.

AB - Abstract Elementary perceptron is an artificial neural network with a single layer of adaptive links and one output neuron that can solve simple linearly separable tasks such as invariant pattern recognition, linear approximation, prediction and others. We report on the hardware realization of the elementary perceptron with the use of polyaniline-based memristive devices as the analog link weights. An error correction algorithm was used to get the perceptron to learn the implementation of the NAND and NOR logic functions as examples of linearly separable tasks. The physical realization of an elementary perceptron demonstrates the ability to form the hardware-based neuromorphic networks with the use of organic memristive devices. The results provide a great promise toward new approaches for very compact, low-volatile and high-performance neurochips that could be made for a huge number of intellectual products and applications.

KW - Machine learning

KW - Memristor

KW - Neuromorphic computing

KW - Pattern classification

KW - Perceptron

KW - Polyaniline

UR - http://www.scopus.com/inward/record.url?scp=84930936504&partnerID=8YFLogxK

U2 - 10.1016/j.orgel.2015.06.015

DO - 10.1016/j.orgel.2015.06.015

M3 - Article

AN - SCOPUS:84930936504

VL - 25

SP - 16

EP - 20

JO - Organic Electronics

JF - Organic Electronics

SN - 1566-1199

M1 - 3127

ER -

ID: 88206478