Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Kyung Jean, Yoon"'
Autor:
Woorham Bae, Kyung Jean Yoon
Publikováno v:
Advanced Intelligent Systems, Vol 2, Iss 5, Pp n/a-n/a (2020)
Herein, a robust programmable stochastic weight generation method for a memristive neural network is proposed. There have been few prior algorithm suggestions for crossbar neural network‐based stochastic learning; however, there has not been much a
Externí odkaz:
https://doaj.org/article/6604d22199354578b814e3fda60a1a36
Autor:
Nuo Xu, Tae Gyun Park, Hae Jin Kim, Xinglong Shao, Kyung Jean Yoon, Tae Hyung Park, Liang Fang, Kyung Min Kim, Cheol Seong Hwang
Publikováno v:
Advanced Intelligent Systems, Vol 2, Iss 1, Pp n/a-n/a (2020)
Stateful logic enables highly energy‐efficient computation because the time and energy consumption for data transfer between the memory and the processing units in the traditional computation system can significantly be saved due to the combined fu
Externí odkaz:
https://doaj.org/article/ef9a4381111f4d60b13298457413979d
Autor:
Seung Soo Kim, Soo Kyeom Yong, Whayoung Kim, Sukin Kang, Hyeon Woo Park, Kyung Jean Yoon, Dong Sun Sheen, Seho Lee, Cheol Seong Hwang
Publikováno v:
Advanced materials (Deerfield Beach, Fla.).
Vertically integrated NAND (V-NAND) flash memory is the main data storage in modern handheld electronic devices, widening its share even in the data centers where installation and operation costs are critical. While the conventional scaling rule has
This paper proposes a in-memory Hamming error-correcting code (ECC) in memristor crossbar array (CBA). Based on unique I-V characteristic of complementary resistive switching (CRS) memristor, this work discovers that a combination of three memristors
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e13a65868276a055b4d17b80c0055b4
https://doi.org/10.36227/techrxiv.16926025.v1
https://doi.org/10.36227/techrxiv.16926025.v1
Autor:
Kyung Jean Yoon, Woorham Bae
Publikováno v:
IEEE Transactions on Nanotechnology. 19:553-564
It can never be overemphasized the importance of understanding noise in electronics. However, it has not been deeply considered in memristor-based circuits and systems, while there have been tons of efforts to utilize the memristors to improve the pr
Autor:
Jessica E. Koehne, Andrew L. Rukhin, Ram P. Gandhiraman, Dongil Lee, Dong-Il Moon, M. Meyyappan, Myeong-Lok Seol, Sun Jin Kim, Kyung Jean Yoon, Beomseok Kim, Jin-Woo Han
Publikováno v:
ACS Applied Electronic Materials. 1:1162-1168
The emerging Internet of things (IoT) demands not only new device technologies but also strengthening the security of things in order to prevent tampering and hacking. Humans have unique characteri...
Autor:
Kyung Jean Yoon, Woorham Bae
Publikováno v:
Advanced Intelligent Systems, Vol 2, Iss 5, Pp n/a-n/a (2020)
Herein, a robust programmable stochastic weight generation method for a memristive neural network is proposed. There have been few prior algorithm suggestions for crossbar neural network‐based stochastic learning; however, there has not been much a
Autor:
Dong-Il Moon, M. Meyyappan, Han Joon Kim, Myeong-Lok Seol, Kyung Jean Yoon, Jin-Woo Han, Cheol Seong Hwang
Publikováno v:
Nanoscale Advances. 1:2990-2998
A method to electrically induce memristor performance from inkjet-printed silver (Ag) nanoparticles is presented, which is effective on a specifically designed hourglass-shaped Ag metal device. Joule heating-induced oxidation in the bottleneck region
Publikováno v:
IEEE Transactions on Circuits and Systems II: Express Briefs. 65:1839-1843
A variation-tolerant and sneak-current-free readout technique for cross-point non-volatile memory is presented. The proposed readout circuit has a sneak current compensation port, which collects sneak current information from multiple unselected cell
Publikováno v:
Nano Energy. 44:82-88
Mechanical energy harvesters have not much benefited from the significant advantages of additive manufacturing techniques because the functional materials are not compatible with most printable schemes. In this work, a triboelectric nanogenerator is