• 제목/요약/키워드: DNU

검색결과 22건 처리시간 0.029초

MICE-LED융합 양방향 미디어아트 인터렉티브 컨텐츠 및 Tele-Screen 기초 연구 (A Study on research interactive contents MICE-LED tele-screen bidirectional media art)

  • 김동식;윤상호;김병오;김상옥
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2015년도 춘계 종합학술대회 논문집
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    • pp.275-276
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    • 2015
  • LED를 활용한 고객 체험형 양방향 디지털 미디어아트 컨텐츠 및 Tele-Screen 솔루션을 통하여 차별화된 서비스가 가능 자연 친화적, 인체 감응 및 상황 인지 기반으로 다수가 참여 가능한 양방향 소통, 감성 디자인이 고려된 콘텐츠를 제공하는 MICE 융합 인터렉티브 LED 미디어아트 콘텐츠 및 플랫폼 기술 개발의 기초 연구를 수행 하고, Tele-Screen개발과 구현 방법을 제안하였다.

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LED가로등의 GUI자동감시시스템에 대한 개선방안 연구 (A Study on performance imporvenment of street light GUI monitoring and control system)

  • 김동식;장영석;김병오;김상옥
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2015년도 춘계 종합학술대회 논문집
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    • pp.279-280
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    • 2015
  • 가로등 무선원격감시제어 시스템의 문제점 분석 및 개선 방안에 대한 분석을 통하여 가로등 효율성 제고 및 무선 원격감시제어 시스템의 안정성을 높이기 위한 가로등 무선원격감시제어 시스템의 문제점의 개선 방안을 연구하고, 도입을 위한 구체적인 절차를 제시하였다. 이러한 불완전한 GUI기반자동감시시스템을 원인 분석하여 문제점을 파악 개선방안을 제안하였다. 또한 원격제어용 GUI기반자동감시시스템 구현 방법을 제안하였다.

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다층 신경회로망을 이용한 비선형 시스템의 견실한 제어 (Robust control of Nonlinear System Using Multilayer Neural Network)

  • 조현섭
    • 한국정보전자통신기술학회논문지
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    • 제6권4호
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    • pp.243-248
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    • 2013
  • In this thesis, we have designed the indirect adaptive controller using Dynamic Neural Units(DNU) for unknown nonlinear systems. Proposed indirect adaptive controller using Dynamic Neural Unit based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

미지의 비선형 시스템 제어를 위한 DNU와 GA알고리즘 적용에 관한 연구 (Dynamic Neural Units and Genetic Algorithms With Applications to the Control of Unknown Nonlinear Systems)

  • ;;조현섭;전정채
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 하계학술대회 논문집 D
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    • pp.2486-2489
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    • 2002
  • Pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

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신경회로망을 이용한 동적 시스템의 자기동조 제어기 설계 (Design of auto-tuning controller for Dynamic Systems using neural networks)

  • 조현섭;오명관
    • 한국산학기술학회:학술대회논문집
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    • 한국산학기술학회 2007년도 춘계학술발표논문집
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    • pp.147-149
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    • 2007
  • "Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

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과도상태 성능 개선을 위한 적응 제어기 설계 (The Adaptation Controller Plan for a Transient State Efficiency Improvement)

  • 조현섭;전호익
    • 한국산학기술학회:학술대회논문집
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    • 한국산학기술학회 2011년도 춘계학술논문집 1부
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    • pp.379-381
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    • 2011
  • Dynamic Neural Unit(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

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Geneo-tic Algorithms를 이용한 비선형 시스템 제어 (Unknown Nonlinear Systems Control Using Genetic Algorithms)

  • 조현섭
    • 한국산학기술학회:학술대회논문집
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    • 한국산학기술학회 2009년도 춘계학술발표논문집
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    • pp.443-445
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    • 2009
  • Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

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DNU에 의한 비선형 동적시스템의 적응제어 (Adaptive Control of Non-linearity Dynamic System using DNU)

  • 조현섭;김희숙
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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    • pp.533-536
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    • 1998
  • The intent of this paper is to describe a neural network structure called dynamic neural processor(DNP), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. Computer simulations are provided to demonstrate the effectiveness of the proposed learning using the DNP.

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동적시스템의 자동동조를 위한 신경망 알고리즘 응용 (Neural Network Algorithm Application to Auto-tuning of Dynamic Systems)

  • 조현섭
    • 한국산학기술학회:학술대회논문집
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    • 한국산학기술학회 2006년도 추계학술발표논문집
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    • pp.186-190
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    • 2006
  • "Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

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적응 신경망을 이용한 동적 매니퓰레이터의 위치제어 설계 (A Desing of position controller for manipulator using Adaptive neural network)

  • 조현섭;유인호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 제38회 하계학술대회
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    • pp.1574-1575
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    • 2007
  • "Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

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