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Artificial optic-neural synapse for colored and color-mixed pattern recognition
The priority of synaptic device researches has been given to prove the device potential for the emulation of synaptic dynamics and not to functionalize further synaptic devices for more complex learning. Here, we demonstrate an optic-neural synaptic device by implementing synaptic and optical-sensin...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6269540/ https://www.ncbi.nlm.nih.gov/pubmed/30504804 http://dx.doi.org/10.1038/s41467-018-07572-5 |
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author | Seo, Seunghwan Jo, Seo-Hyeon Kim, Sungho Shim, Jaewoo Oh, Seyong Kim, Jeong-Hoon Heo, Keun Choi, Jae-Woong Choi, Changhwan Oh, Saeroonter Kuzum, Duygu Wong, H.-S. Philip Park, Jin-Hong |
author_facet | Seo, Seunghwan Jo, Seo-Hyeon Kim, Sungho Shim, Jaewoo Oh, Seyong Kim, Jeong-Hoon Heo, Keun Choi, Jae-Woong Choi, Changhwan Oh, Saeroonter Kuzum, Duygu Wong, H.-S. Philip Park, Jin-Hong |
author_sort | Seo, Seunghwan |
collection | PubMed |
description | The priority of synaptic device researches has been given to prove the device potential for the emulation of synaptic dynamics and not to functionalize further synaptic devices for more complex learning. Here, we demonstrate an optic-neural synaptic device by implementing synaptic and optical-sensing functions together on h-BN/WSe(2) heterostructure. This device mimics the colored and color-mixed pattern recognition capabilities of the human vision system when arranged in an optic-neural network. Our synaptic device demonstrates a close to linear weight update trajectory while providing a large number of stable conduction states with less than 1% variation per state. The device operates with low voltage spikes of 0.3 V and consumes only 66 fJ per spike. This consequently facilitates the demonstration of accurate and energy efficient colored and color-mixed pattern recognition. The work will be an important step toward neural networks that comprise neural sensing and training functions for more complex pattern recognition. |
format | Online Article Text |
id | pubmed-6269540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62695402018-12-03 Artificial optic-neural synapse for colored and color-mixed pattern recognition Seo, Seunghwan Jo, Seo-Hyeon Kim, Sungho Shim, Jaewoo Oh, Seyong Kim, Jeong-Hoon Heo, Keun Choi, Jae-Woong Choi, Changhwan Oh, Saeroonter Kuzum, Duygu Wong, H.-S. Philip Park, Jin-Hong Nat Commun Article The priority of synaptic device researches has been given to prove the device potential for the emulation of synaptic dynamics and not to functionalize further synaptic devices for more complex learning. Here, we demonstrate an optic-neural synaptic device by implementing synaptic and optical-sensing functions together on h-BN/WSe(2) heterostructure. This device mimics the colored and color-mixed pattern recognition capabilities of the human vision system when arranged in an optic-neural network. Our synaptic device demonstrates a close to linear weight update trajectory while providing a large number of stable conduction states with less than 1% variation per state. The device operates with low voltage spikes of 0.3 V and consumes only 66 fJ per spike. This consequently facilitates the demonstration of accurate and energy efficient colored and color-mixed pattern recognition. The work will be an important step toward neural networks that comprise neural sensing and training functions for more complex pattern recognition. Nature Publishing Group UK 2018-11-30 /pmc/articles/PMC6269540/ /pubmed/30504804 http://dx.doi.org/10.1038/s41467-018-07572-5 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Seo, Seunghwan Jo, Seo-Hyeon Kim, Sungho Shim, Jaewoo Oh, Seyong Kim, Jeong-Hoon Heo, Keun Choi, Jae-Woong Choi, Changhwan Oh, Saeroonter Kuzum, Duygu Wong, H.-S. Philip Park, Jin-Hong Artificial optic-neural synapse for colored and color-mixed pattern recognition |
title | Artificial optic-neural synapse for colored and color-mixed pattern recognition |
title_full | Artificial optic-neural synapse for colored and color-mixed pattern recognition |
title_fullStr | Artificial optic-neural synapse for colored and color-mixed pattern recognition |
title_full_unstemmed | Artificial optic-neural synapse for colored and color-mixed pattern recognition |
title_short | Artificial optic-neural synapse for colored and color-mixed pattern recognition |
title_sort | artificial optic-neural synapse for colored and color-mixed pattern recognition |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6269540/ https://www.ncbi.nlm.nih.gov/pubmed/30504804 http://dx.doi.org/10.1038/s41467-018-07572-5 |
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