Jong-Ho Bae
Orcid: 0000-0002-1786-7132
According to our database1,
Jong-Ho Bae
authored at least 21 papers
between 2017 and 2024.
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Bibliography
2024
Sensors, June, 2024
Si-Based Dual-Gate Field-Effect Transistor Array for Low-Power On-Chip Trainable Hardware Neural Networks.
Adv. Intell. Syst., January, 2024
Improvement of the Symmetry and Linearity of Synaptic Weight Update by Combining the InGaZnO Synaptic Transistor and Memristor.
IEEE Access, 2024
2023
Analog Synaptic Devices Based on IGZO Thin-Film Transistors with a Metal-Ferroelectric-Metal-Insulator-Semiconductor Structure for High-Performance Neuromorphic Systems.
Adv. Intell. Syst., December, 2023
1/<i>f</i> Noise in Synaptic Ferroelectric Tunnel Junction: Impact on Convolutional Neural Network.
Adv. Intell. Syst., June, 2023
IEEE Access, 2023
2021
On-chip trainable hardware-based deep Q-networks approximating a backpropagation algorithm.
Neural Comput. Appl., 2021
Hardware-based spiking neural network architecture using simplified backpropagation algorithm and homeostasis functionality.
Neurocomputing, 2021
CoRR, 2021
Spiking Neural Networks With Time-to-First-Spike Coding Using TFT-Type Synaptic Device Model.
IEEE Access, 2021
Threshold-Variation-Tolerant Coupling-Gate α-IGZO Synaptic Transistor for More Reliably Controllable Hardware Neuromorphic System.
IEEE Access, 2021
Vertical and lateral charge losses during short time retention in 3-D NAND flash memory.
Proceedings of the 51st IEEE European Solid-State Device Research Conference, 2021
2020
Efficient precise weight tuning protocol considering variation of the synaptic devices and target accuracy.
Neurocomputing, 2020
Low-Power and High-Density Neuron Device for Simultaneous Processing of Excitatory and Inhibitory Signals in Neuromorphic Systems.
IEEE Access, 2020
Proceedings of the 2020 Device Research Conference, 2020
2019
Adaptive learning rule for hardware-based deep neural networks using electronic synapse devices.
Neural Comput. Appl., 2019
Investigation of Neural Networks Using Synapse Arrays Based on Gated Schottky Diodes.
Proceedings of the International Joint Conference on Neural Networks, 2019
A Spiking Neural Network with a Global Self-Controller for Unsupervised Learning Based on Spike-Timing-Dependent Plasticity Using Flash Memory Synaptic Devices.
Proceedings of the International Joint Conference on Neural Networks, 2019
Proceedings of the 49th European Solid-State Device Research Conference, 2019
2018
Proceedings of the IEEE International Symposium on Circuits and Systems, 2018
2017
Adaptive Learning Rule for Hardware-based Deep Neural Networks Using Electronic Synapse Devices.
CoRR, 2017