Artificial neuromodulator–synapse mimicked by a three-terminal vertical organic ferroelectric barristor for fast and energy-efficient neuromorphic computing-Reference-Cited by-同舟云学术

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Artificial neuromodulator–synapse mimicked by a three-terminal vertical organic ferroelectric barristor for fast and energy-efficient neuromorphic computing

Published:2024-06 Issue: Volume:124 Page:109435
ISSN:2211-2855
Container-title:Nano Energy
language:en
Short-container-title:Nano Energy

Author:

Ham Seonggil,Jang Jingon,Koo Dohyong,Gi Sanggyun,Kim Dowon,Jang Seonghoon,Kim Nam Dong,Bae Sukang,Lee Byunggeun,Lee Chul-Ho,Wang Gunuk

Funder

Korea University

Kwangwoon University

Korea Ministry of Education

National Research Foundation of Korea

IITP

KU-KIST Graduate School of Converging Science and Technology

Publisher

Elsevier BV

Reference56 articles.

1. Deep learning;LeCun;Nature,2015

2. Towards artificial general intelligence with hybrid Tianjic chip architecture;Pei;Nature,2019

3. Analogue signal and image processing with large memristor crossbars;Li;Nat. Electron.,2017

4. An analysis of convolutional neural networks for image classification;Sharma;Procedia Comput. Sci.,2018

5. Convolutional neural networks for speech recognition;Abdel-Hamid;IEEE ACM Trans. Audio Speech Lang. Process.,2014

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