• 제목/요약/키워드: Competitive Layer

검색결과 97건 처리시간 0.026초

Ti-Si 계면의 얇은 산화막이 TiN/TiS$i_2$ 이중구조막 형성에 미치는 영향 (Effects of the thin SiO$_{2}$ film at the Ti-Si interface on the formation of TiN/TiS$i_2$ bilayer)

  • 이철진;성만영;성영권
    • 대한전기학회논문지
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    • 제45권2호
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    • pp.242-248
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    • 1996
  • The properties of TiN/TiSi$_{2}$ bilayer formed by a rapid thermal annealing is investigated when thin SiO$_{2}$ film exists at the Ti-Si interface. The competitive reaction for the TiN/TiSi_2 bilayer occurs above 600 .deg. C. The thickness of the TiSi$_{2}$ layer decreases with increasing SiO$_{2}$ film thickness and also decreases with increasing anneal temperture When the competitive reaction for the TiN/TiSi$_{2}$ bilayer is occured by rapid thermal annealing, the composition of TiN layer represents TiN$_{x}$O$_{y}$ due to the SiO$_{2}$ layer at the Ti-Si interface but the structures of the TiN and TiSi$_{2}$ layers were not changed.d.d.

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Counterpropagation 알고리즘에서 퍼지 제어 기법을 이용한 경쟁층 설정 방법 (Setting Method of Competitive Layer using Fuzzy Control Method for Enhanced Counterpropagation Algorithm)

  • 김광백
    • 한국정보통신학회논문지
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    • 제15권7호
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    • pp.1457-1464
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    • 2011
  • 본 논문에서는 개선된 CP 알고리즘에서 경쟁층의 수를 효율적으로 설정하기 위해 퍼지 제어 기법을 이용하여 경쟁층의 수를 결정하는 방법을 제안한다. 제안된 방법은 CP 알고리즘에 입력되는 패턴의 정보를 이용하여 퍼지 소속 함수를 설계하고 입력에 대한 소속도를 계산한 후, 퍼지 제어 규칙을 적용하고, Mamdani의 Max_Min 추론 방법으로 추론한다. 퍼지 추론을 통해 최종적으로 얻어진 값을 무게 중심법으로 비퍼지화 하여 최종적으로 개선된 CP 알고리즘의 경쟁층의 수를 결정하는데 적용한다. 제안된 방법의 학습 및 인식 성능을 평가하기 위해, 영문과 같이 다양한 패턴을 실험에 적용한 결과, 제안된 방법이 경쟁층의 수를 결정하는데 효과적임을 확인할 수 있었다.

${NH}_{3}$ 분위기에서 급속열처리에 의한 TiN/${TiSi}_{2}$ 이중구조막의 특성에 대한 고찰 (A Study on the Properties of TiN/${TiSi}_{2}$ Bilayer by a Rapid Thermal Anneal in ${NH}_{3}$ Ambient)

  • 이철진;성영권
    • 대한전기학회논문지
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    • 제41권8호
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    • pp.869-874
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    • 1992
  • The physical and electrical properties of TiN/TiSiS12T bilayer were studied. The TiN/TiSiS12T bilayer was formed by rapid thermal anneal in NHS13T ambient after the Ti film was deposited on silicon substrate. The Ti film reacts with NHS13T gas to make a TiN layer at the surface and reacts with silicon to make a TiSiS12T layer at the interface respectively. It was found that the formation of TiN/TiSiS12T bilayer depends on RTA temperature. In this experiment, competitive reaction for TiN/TiSiS12T bilayer occured above $600^{\circ}C$. Ti-rich TiNS1xT layer and Ti-rich TiSiS1xT layer and Ti-rich TiSiS1xT layer were formed at $600^{\circ}C$. stable structure TiN layer TiSiS12T layer which has CS149T phase and CS154T phase were formed at $700^{\circ}C$. Both stable TiN layer and CS154T phase TiSiS12T layer were formed at 80$0^{\circ}C$. The thickness of TiN/TiSiS12T bilayer was increased as the thickness of deposited Ti film increased.

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급속열처리에 의한 $TiN/TiSi_2$ 이중구조막 혈성에 대한 Ti-Si 계면의 얇은 산화막의 영향 (Effects of the thin $SiO_2$ film on the formation of $TiN/TiSi_2$ bilayer formed by rapid thermal annealing)

  • 이철진;성만영;성영권
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1994년도 하계학술대회 논문집 C
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    • pp.1223-1225
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    • 1994
  • The properties of $TiN/TiSi_2$ bilayer formed by a rapid thermal anneal ing is investigated when thin $SiO_2$ film exists at the Ti-Si interface. The competitive reaction for the $TiN/TiSi_2$ bilayer occurs above $600^{\circ}C$. The thickness of the $TiSi_2$ layer decreases with increasing $SiO_2$ film thickness while the TiN layer increases at the competitive reaction. The composition of TiN layer is changed to the $TiN_xO_y$ film due to the thin $SiO_2$ layer at the Ti-Si interface while the structure of the TiN and $TiSi_2$ layers was not changed.

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가변 출력층 구조의 경쟁학습 신경회로망을 이용한 패턴인식 (Pattern recognition using competitive learning neural network with changeable output layer)

  • 정성엽;조성원
    • 전자공학회논문지B
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    • 제33B권2호
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    • pp.159-167
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    • 1996
  • In this paper, a new competitive learning algorithm called dynamic competitive learning (DCL) is presented. DCL is a supervised learning mehtod that dynamically generates output neuraons and nitializes weight vectors from training patterns. It introduces a new parameter called LOG (limit of garde) to decide whether or not an output neuron is created. In other words, if there exist some neurons in the province of LOG that classify the input vector correctly, then DCL adjusts the weight vector for the neuraon which has the minimum grade. Otherwise, it produces a new output neuron using the given input vector. It is largely learning is not limited only to the winner and the output neurons are dynamically generated int he trining process. In addition, the proposed algorithm has a small number of parameters. Which are easy to be determined and applied to the real problems. Experimental results for patterns recognition of remote sensing data and handwritten numeral data indicate the superiority of dCL in comparison to the conventional competitive learning methods.

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Supervised Competitive Learning Neural Network with Flexible Output Layer

  • Cho, Seong-won
    • 한국지능시스템학회논문지
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    • 제11권7호
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    • pp.675-679
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    • 2001
  • In this paper, we present a new competitive learning algorithm called Dynamic Competitive Learning (DCL). DCL is a supervised learning method that dynamically generates output neurons and initializes automatically the weight vectors from training patterns. It introduces a new parameter called LOG (Limit of Grade) to decide whether an output neuron is created or not. If the class of at least one among the LOG number of nearest output neurons is the same as the class of the present training pattern, then DCL adjusts the weight vector associated with the output neuron to learn the pattern. If the classes of all the nearest output neurons are different from the class of the training pattern, a new output neuron is created and the given training pattern is used to initialize the weight vector of the created neuron. The proposed method is significantly different from the previous competitive learning algorithms in the point that the selected neuron for learning is not limited only to the winner and the output neurons are dynamically generated during the learning process. In addition, the proposed algorithm has a small number of parameters, which are easy to be determined and applied to real-world problems. Experimental results for pattern recognition of remote sensing data and handwritten numeral data indicate the superiority of DCL in comparison to the conventional competitive learning methods.

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정밀 다층 박막 도금을 이용한 빠른 동작 퓨즈 특성 설계 (Design of Fast Acting Fuse Characteristics Using a Precision Multi-layer Thin Film Plating)

  • 김은민;강창룡
    • 전기학회논문지
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    • 제65권3호
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    • pp.445-451
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    • 2016
  • General fuse elements of solution for fast acting operation characteristics made using silver or silver alloy, those are not able to dominate cost competition to the advanced global leaders that have not only high technology but competitive price. In this study, the method that compose the fuse elements manufactured solution of fast acting operation characteristics by using precision multi-layer thin film plating and helical cutting process from low-priced copper metal. Furthermore, in order to move rated current line of fuse due to the heat loses, the manufacture construction method of fixed resistor is introduced, and then Ni-P plating layer and Sn plating layer are introduced multiply for controling fine opening time characteristics. So this study can establish the high productive and low-priced production method.

경쟁적 퍼지다항식 뉴런에 기초한 고급 자기구성 뉴럴네트워크 (Advanced Self-Organizing Neural Networks Based on Competitive Fuzzy Polynomial Neurons)

  • 박호성;박건준;이동윤;오성권
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권3호
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    • pp.135-144
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    • 2004
  • In this paper, we propose competitive fuzzy polynomial neurons-based advanced Self-Organizing Neural Networks(SONN) architecture for optimal model identification and discuss a comprehensive design methodology supporting its development. The proposed SONN dwells on the ideas of fuzzy rule-based computing and neural networks. And it consists of layers with activation nodes based on fuzzy inference rules and regression polynomial. Each activation node is presented as Fuzzy Polynomial Neuron(FPN) which includes either the simplified or regression polynomial fuzzy inference rules. As the form of the conclusion part of the rules, especially the regression polynomial uses several types of high-order polynomials such as linear, quadratic, and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership (unction are studied and the number of the premise input variables used in the rules depends on that of the inputs of its node in each layer. We introduce two kinds of SONN architectures, that is, the basic and modified one with both the generic and the advanced type. Here the basic and modified architecture depend on the number of input variables and the order of polynomial in each layer. The number of the layers and the nodes in each layer of the SONN are not predetermined, unlike in the case of the popular multi-layer perceptron structure, but these are generated in a dynamic way. The superiority and effectiveness of the Proposed SONN architecture is demonstrated through two representative numerical examples.

Effects of the Ag Layer Embedded in NIZO Layers as Transparent Conducting Electrodes for Liquid Crystal Displays

  • Oh, Byeong-Yun;Heo, Gi-Seok
    • Transactions on Electrical and Electronic Materials
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    • 제17권1호
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    • pp.33-36
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    • 2016
  • In the present work, a Ni-doped indium zinc oxide (NIZO) film and its multilayers with Ag layers were investigated as transparent conducting electrodes for liquid crystal display (LCD) applications, as a substitute for indium tin oxide (ITO) electrodes. By interposing the Ag layer between the NIZO layers, the loss of the optical transmittance occurred; however, the Ag layer brought enhancement of electrical sheet resistance to the NIZO/Ag/NIZO multilayer electrode. The twisted nematic cell based on the NIZO/Ag/NIZO multilayer electrode exhibited superior electro-optical characteristics than those based on single NIZO electrode and was competitive compared to those based on the conventional ITO electrode. An LCD-based NIZO/Ag/NIZO multilayer electrode may allow new approaches to conventional ITO electrodes in display technology.

제강슬래그와 폐아스팔트를 활용한 중온 아스팔트 포장의 거동 분석 (Experimental and Numerical Analysis of Warm Mix Asphalt Pavement prepared using Steel Slag and RAP)

  • 이호정;장동복;김현욱;김인태;김기병;이재훈
    • 한국도로학회논문집
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    • 제19권2호
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    • pp.55-65
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    • 2017
  • PURPOSES : This study aimed to analyze the experimental and numerical behavior of warm mix asphalt pavement prepared using steel slag and RAP and to conduct economic analysis of pavement construction. METHODS : For developing high performance asphalt pavement, we performed three evaluations: fundamental analysis, experimental testing, and 3D finite element analysis. In particular, 3D finite element analysis was conducted on several pavement structures by adopting the results of experimental tests. RESULTS : Through the various evaluations, it was established that steel slag was effective for use as asphalt mixture aggregate. Moreover, asphalt mixture constituting steel slag and RAP demonstrated higher performance behavior compared with conventionally used asphalt mixture. Furthermore, based on the 3D FE modeling, we established that the developed asphalt pavement constituting steel slag and RAP can be utilized for thin layer pavement with comparable performance behavior. CONCLUSIONS :Warm mix asphalt pavement prepared using steel slag and RAP is more competitive and economic compared to hot-mix asphalt pavement. Moreover, it can be applied for preparing thin layer asphalt pavements with reasonable performance. The developed warm mix asphalt pavement prepared using steel slag and RAP can be an alternative pavement type with competitive performance based on the reasonable economic benefit it provides.