Byung-Geun Lee

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Using memristor devices as synaptic connections has been suggested with different neural architectures in the literature. Most of the published works focus on simulating some plasticity mechanism for changing memristor conductance. This paper presents a neural architecture of a character recognition neural system using(More)
This paper presents a neuromorphic system for visual pattern recognition realized in hardware. A new learning rule based on modified spike-timing-dependent plasticity is also presented and implemented with passive synaptic devices. The system includes an artificial photoreceptor, a Pr<sub>0.7</sub>Ca<sub>0.3</sub>MnO<sub>3</sub>-based memristor array, and(More)
Memristive synapses, the most promising passive devices for synaptic interconnections in artificial neural networks, are the driving force behind recent research on hardware neural networks. Despite significant efforts to utilize memristive synapses, progress to date has only shown the possibility of building a neural network system that can classify simple(More)
We report oxide based analog synpase for neuromorphic system. By optimizing redox reaction at the metal/oxide interface, we can obtain stable analog synapse characteristics and wafer scale switching uniformity. We have confirmed the feasibility of neuromorphic hardware system with oxide synapse array device which recognizes the electroencephalogram (EEG)(More)
In this paper, we propose a background subtraction (BGS) method based on the Gaussian mixture models using color and depth information. For combining color and depth information, we used the probabilistic model based on Gaussian distribution. In particular, we focused on solving color camouflage problem and depth denoising. For evaluating our method, we(More)
Efforts to develop scalable learning algorithms for implementation of networks of spiking neurons in silicon have been hindered by the considerable footprints of learning circuits, which grow as the number of synapses increases. Recent developments in nanotechnologies provide an extremely compact device with low-power consumption.In particular, nanoscale(More)
BACKGROUND Cardiac disease is one of the main causes of catastrophic mortality. Therefore, detecting the symptoms of cardiac disease as early as possible is important for increasing the patient's survival. In this study, a compact and effective architecture for detecting atrial fibrillation (AFib) and myocardial ischemia is proposed. We developed a portable(More)
We report novel nanoscale synapse and neuron devices for ultra-high density neuromorphic system. By adopting a Mo electrode, the redox reaction at Mo/Pr<sub>0.7</sub>Ca<sub>0.3</sub>MnO<sub>3</sub> (PCMO) interface was controlled which in turn significantly improve synapse characteristics such as switching uniformity, disturbance, retention and multi-level(More)
We propose a new capacitive microinclinometer where oblique comb electrodes and double-folded suspension springs are aligned parallel to the vertical (111) plane of (110) silicon. The oblique comb utilizes both the overlapped area and the gap between movable and stationary electrodes, resulting in a considerable increase in sensitivity (capacitance(More)
This letter presents an investigation of analog synapse characteristics of a PCMO-based interface switching device with varying electrode materials. In comparison with the filamentary switching device having only 1-b storage and variability issues, the interface switching devices exhibit excellent electrical properties, such as 5-b (32-level) multi-level(More)