文献
J-GLOBAL ID:202202246845344347
整理番号:22A1163820
RRAMベースニューロモルフィックシステムにおける実時間オンライン学習のための高速重み転送法【JST・京大機械翻訳】
A Fast Weight Transfer Method for Real-Time Online Learning in RRAM-Based Neuromorphic System
著者 (4件):
Kim Min-Hwi
(Inter-University of Semiconductor Research Center (ISRC) and Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea)
,
Lee Sin-Hyung
(School of Electronics Engineering, School of Electronic, and School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea)
,
Kim Sungjun
(Division of Electronics and Electrical Engineering, Dongguk University, Seoul, South Korea)
,
Park Byung-Gook
(Inter-University of Semiconductor Research Center (ISRC) and Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea)
資料名:
IEEE Access
(IEEE Access)
巻:
10
ページ:
37030-37038
発行年:
2022年
JST資料番号:
W2422A
ISSN:
2169-3536
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)