Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Heebum Kang"'
Autor:
Seonuk Jeon, Heebum Kang, Hyunjeong Kwak, Kyungmi Noh, Seungkun Kim, Nayeon Kim, Hyun Wook Kim, Eunryeong Hong, Seyoung Kim, Jiyong Woo
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-7 (2023)
Abstract The multilevel current states of synaptic devices in artificial neural networks enable next-generation computing to perform cognitive functions in an energy-efficient manner. Moreover, considering large-scale synaptic arrays, multiple states
Externí odkaz:
https://doaj.org/article/9bf5e1c30916423e96a03aa91d3f24ff
Publikováno v:
AIP Advances, Vol 13, Iss 1, Pp 015318-015318-6 (2023)
This paper investigated the conductance-state stability of TiN/PrCaMnOx (PCMO)-based resistive random-access memory (RRAM), which serves as a kernel weight element in convolutional neural networks (CNNs), to realize accurate feature extraction from i
Externí odkaz:
https://doaj.org/article/7cb3346d0edb423998fcc60551afc81e
Publikováno v:
IEEE Journal of the Electron Devices Society, Vol 10, Pp 397-401 (2022)
The reversible transition between the on and off states of threshold switches under a constant pulse generates voltage oscillation, which can be exploited for compact neuron element in neuromorphic systems. Because the transition voltages play an imp
Externí odkaz:
https://doaj.org/article/3010596c3ff342e6a8d68a91940b5987
Publikováno v:
Frontiers in Nanotechnology, Vol 4 (2022)
While electro-chemical RAM (ECRAM)-based cross-point synaptic arrays are considered to be promising candidates for energy-efficient neural network computational hardware, array-level analyses to achieve energy-efficient update operations have not yet
Externí odkaz:
https://doaj.org/article/1ea9d91868d84a0f80bca79eac3c0809
Autor:
Heebum Kang, Jongseon Seo, Hyejin Kim, Hyun Wook Kim, Eun Ryeong Hong, Nayeon Kim, Daeseok Lee, Jiyong Woo
Publikováno v:
Micromachines, Vol 13, Iss 3, p 453 (2022)
To enhance the computing efficiency in a neuromorphic architecture, it is important to develop suitable memory devices that can emulate the role of biological synapses. More specifically, not only are multiple conductance states needed to be achieved
Externí odkaz:
https://doaj.org/article/3023484688a44eb1ab0320dc55fdf38e
Publikováno v:
IEEE Transactions on Electron Devices. 70:3031-3036
Publikováno v:
IEEE Transactions on Electron Devices. 70:1659-1663
Publikováno v:
2022 IEEE Silicon Nanoelectronics Workshop (SNW).
Publikováno v:
2022 6th IEEE Electron Devices Technology & Manufacturing Conference (EDTM).
The explosive growth of data and information has motivated technological developments in computing systems that utilize them for efficiently discovering patterns and gaining relevant insights. Inspired by the structure and functions of biological syn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2fddf5cb8b22bb6945aa24c0a1a9994
https://doi.org/10.22541/au.163638373.32437243/v1
https://doi.org/10.22541/au.163638373.32437243/v1