Study on battery-like synapse device with high linearity and wide dynamic range for a high efficient neuromorphic computing고효율 뉴로모픽 컴퓨팅을 위한 고선형성, 넓은 동적범위 특성의 배터리-기작 시냅스 소자 연구

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With the recent high demand for "big data processing", bio-inspired synapse devices based on the resistive switching, which mimics the nervous system of the brain, have attracted attention. To emulate the brain's synaptic plasticity, various mechanisms of synapse devices have been studied, but the factors such as non-linearity, asymmetry, and low dynamic range degrade critically the performance of neuromorphic computing. In this study, we proposed a three-terminal architecture of battery-like organic synapse (HBOS) device utilizing acidic hydrogel electrolyte PVA with high linearity (<2.54), wide dynamic range (>450), and analog resistance change characteristics for the application of highly efficient neuromorphic computing with artificial neural network based on a battery mechanism. Based on the understanding of electrical properties and qualitative analysis, we suggested a programming strategy that improves linear (<1) and symmetric synapse characteristics with less energy consumption. Furthermore, with artificial neural network simulations, we validated the suggested technique, which exhibits a value of MNIST maximum recognition rate of real-case (92.68%) highly closed to the ideal case (93.7%).
Advisors
Kim, Kyung Minresearcher김경민researcher
Description
한국과학기술원 :신소재공학과,
Publisher
한국과학기술원
Issue Date
2021
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 신소재공학과, 2021.8,[xii, 66 p. :]

Keywords

Battery-like organic synapse device▼aSynaptic plasticity▼aHigh linearity▼aSymmetry▼aWide dynamic range▼aNeuromorphic computing▼aAnalog resistive switching▼aArtificial neural network; 배터리 기작 유기 시냅스 소자▼a시냅스 가소성▼a고 선형성▼a대칭성▼a넓은 동적범위▼a뉴로모픽 컴퓨팅▼a아날로그 저항 변화▼a인공 신경망

URI
http://hdl.handle.net/10203/295419
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=963533&flag=dissertation
Appears in Collection
MS-Theses_Master(석사논문)
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