K
Kibong Moon
Researcher at Pohang University of Science and Technology
Publications - 43
Citations - 2444
Kibong Moon is an academic researcher from Pohang University of Science and Technology. The author has contributed to research in topics: Neuromorphic engineering & Resistive random-access memory. The author has an hindex of 20, co-authored 42 publications receiving 1731 citations.
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Journal ArticleDOI
Neuromorphic computing using non-volatile memory
Geoffrey W. Burr,Robert M. Shelby,Abu Sebastian,Sangbum Kim,Seyoung Kim,Severin Sidler,Kumar Virwani,Masatoshi Ishii,Pritish Narayanan,Alessandro Fumarola,Lucas L. Sanches,Irem Boybat,Manuel Le Gallo,Kibong Moon,Jiyoo Woo,Hyunsang Hwang,Yusuf Leblebici +16 more
TL;DR: The relevant virtues and limitations of these devices are assessed, in terms of properties such as conductance dynamic range, (non)linearity and (a)symmetry of conductance response, retention, endurance, required switching power, and device variability.
Journal ArticleDOI
Improved Synaptic Behavior Under Identical Pulses Using AlO x /HfO 2 Bilayer RRAM Array for Neuromorphic Systems
Jiyong Woo,Kibong Moon,Jeonghwan Song,Sangheon Lee,Myounghun Kwak,Jaesung Park,Hyunsang Hwang +6 more
TL;DR: A linear potentiation behavior of conductance under identical pulses is demonstrated using the effect of barrier layer on the switching, which was realized by fabricating an RRAM on top of an Al electrode.
Journal ArticleDOI
TiO x -Based RRAM Synapse With 64-Levels of Conductance and Symmetric Conductance Change by Adopting a Hybrid Pulse Scheme for Neuromorphic Computing
TL;DR: In this paper, the authors proposed a TiO x-based resistive switching device for neuromorphic synapse applications, which is capable of 64-levels conductance states because of their optimized interface between the metal electrode and the TiO X film.
Journal ArticleDOI
RRAM-based synapse devices for neuromorphic systems
Kibong Moon,Seokjae Lim,Jae-Hoon Park,Changhyuck Sung,Sang Ho Oh,Jiyong Woo,Jin Yong Lee,Hyunsang Hwang +7 more
TL;DR: It is confirmed thatsynapse device characteristics directly affect the pattern recognition accuracy of ANNs, and a 3-terminal synapse device or a device based on a new operation principle should be developed as an alternative for on-chip training applications.
Journal ArticleDOI
Various Threshold Switching Devices for Integrate and Fire Neuron Applications
Donguk Lee,Myonghoon Kwak,Kibong Moon,Wooseok Choi,Jaehyuk Park,Jongmyung Yoo,Jeonghwan Song,Seokjae Lim,Changhyuck Sung,Writam Banerjee,Hyunsang Hwang +10 more
TL;DR: This study demonstrates an integrate and fire (I&F) neuron using threshold switching (TS) devices to implement spike‐based neuromorphic system and indicates applicability of TS‐based I&F neuron in neuromorphic hardware application.