Sang-Gyun Gi

A Learning‐Rate Modulable and Reliable TiO<i>_x</i> Memristor Array for Robust, Fast, and Accurate Neuromorphic Computing

Jingon Jang, Sang-Gyun Gi, Injune Yeo et al. · Advanced Science · 2022 · 67 citations · Full text

Engineering, Computer Engineering, Electrical Engineering +14

Analog Synapse Device With 5-b MLC and Improved Data Retention for Neuromorphic System

Kibong Moon, Euijun Cha, Jaesung Park et al. · IEEE Electron Device Letters · 2016 · 52 citations

Engineering, Materials Engineering, Materials Science +13

Stuck-at-Fault Tolerant Schemes for Memristor Crossbar Array-Based Neural Networks

Injune Yeo, Myonglae Chu, Sang-Gyun Gi et al. · IEEE Transactions on Electron Devices · 2019 · 52 citations

Engineering, Computer Engineering, Electrical Engineering +17

High density neuromorphic system with Mo/Pr0.7Ca0.3MnO3 synapse and NbO2 IMT oscillator neuron

Kibong Moon, Euijun Cha, Jaesung Park et al. · 2015 · 47 citations

Life Sciences, Materials Engineering, Materials Science +15

WO_x-Based Synapse Device With Excellent Conductance Uniformity for Hardware Neural Networks

Wooseok Choi, Sang-Gyun Gi, Donguk Lee et al. · IEEE Transactions on Nanotechnology · 2020 · 18 citations

Engineering, Electrical Engineering, Materials Science +17