Demonstration of advanced neuromorphic computing using low current memristive arrays저전류 멤리스티브 어레이를 사용한 고급 뉴로모픽 컴퓨팅 시연 연구

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dc.contributor.advisorKim, Kyung Min-
dc.contributor.advisor김경민-
dc.contributor.authorCheong, Woon Hyung-
dc.date.accessioned2023-06-22T19:33:55Z-
dc.date.available2023-06-22T19:33:55Z-
dc.date.issued2023-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1030487&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/308579-
dc.description학위논문(박사) - 한국과학기술원 : 신소재공학과, 2023.2,[vi, 95 p. :]-
dc.description.abstractAs artificial intelligence technology using artificial neural networks develops, the development of new computing methods using memristors, which are resistive switching elements, is being promoted. However, not much research has been done to demonstrate the operation of memristors on an array basis. In this dissertation, a demonstration of the operation of a network based on a memristor crossbar array was demonstrated, and at the same time, an energy efficient network was constructed by developing an algorithm that mimics the brain. In addition, based on material properties, dynamic routings in artificial neural network topology were made, enabling advanced computing techniques to be directly operated in hardware.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectMemristor▼aArtificial neural network▼aResistive switching▼aECM memristor▼aCTM memristor▼aSimulation-
dc.subject멤리스터▼a인공 신경망▼a저항성 스위칭▼aECM 멤리스터▼aCTM 멤리스터▼a시뮬레이션-
dc.titleDemonstration of advanced neuromorphic computing using low current memristive arrays-
dc.title.alternative저전류 멤리스티브 어레이를 사용한 고급 뉴로모픽 컴퓨팅 시연 연구-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :신소재공학과,-
dc.contributor.alternativeauthor정운형-
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MS-Theses_Ph.D.(박사논문)
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