• 대한전자공학회논문지TE
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• 제39권2호
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• pp.66-75
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• 2002

본 논문에서는 역전파 신경회로망의 학습능률을 향상시키기 위한 방법으로 발생한 오차에 따라서 학습파라미터와 은닉층의 수를 적응적으로 변경시킬 수 있는 적응 역 전파 학습알고리즘을 제안하였다. 제안한 알고리즘은 역전파 신경회로망이 국소점으로 수렴하는 문제를 해결할 수 있고 최적의 수렴환경을 만들 수 있다. 제안된 알고리즘을 평가하기 위하여 배타적 논리합, 3-패리티 및 7${\times}$5 영문자 폰트의 학습을 이용하였다. 실험결과, 기존에 제안된 알고리즘들에 비하여 국소점에 빠지게 되는 경우가 감소하였고 약 17.6%~64.7%정도 학습능률이 향상하였다.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2005년도 추계학술발표회
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• pp.832-833
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• 2005

• 한국진공학회:학술대회논문집
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• 한국진공학회 2015년도 제49회 하계 정기학술대회 초록집
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• pp.211.2-211.2
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• 2015

In order to investigate the effect of front channel in DAL (dual active layer) TFT (thin film transistor), we successfully fabricated DAL TFT composed of ITZO and IGZO as active layer using the solution process. In this structure, ITZO and IGZO active layer were used as front and back channel, respectively. The front channel was changed from 0.05 to 0.2 M at fixed 0.3 M IGZO of back channel. When the mol concentration of front channel was increased, the threshold voltage (VTH) was increased from 2.0 to -11.9 V and off current also was increased from 10-12 to 10-11. This phenomenon is due to increasing the carrier concentration by increasing the volume of the front channel. The saturation mobility of DAL TFT with 0.05, 0.1, and 0.2 M ITZO were 0.45, 4.3, and $0.65cm2/V{\cdot}s$. Even though 0.2 M ITZO has higher carrier concentration than 0.05 and 0.1 M ITZO, the 0.1 M ITZO/0.3 M IGZO DAL TFT has the highest saturation mobility. This is due to channel defect such as pores and pin-holes. These defect sites were created during deposition process by solvent evaporation. Due to these defect sites, the 0.1 M ITZO/0.3 M IGZO DAL TFT shows the higher saturation mobility than that of DAL TFT with front channel of 0.2 M ITZO.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 C
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• pp.1824-1826
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• 2000

Up to date, the dual scanning method has been adopted to decrease address-ing period in AC PDP. In this case, addressing period can be reduced, but the driving circuit cost should be increased. In this study, to increase addressing speed we have studied the relationship between addressing speed and cell structure. That is to say, we varied the thickness of dielectric layer on the front glass, the thickness of white back and the height of barrier rib on the rear glass. So, we found that the addressing time was decreased 4% with decreasing 5um thickness of dielectric layer on the front glass and 2um thickness of white back on the rear glass. Also in case of decreasing the height of barrier rib, addressing time was decreased about 4% per 10um.

• 전자공학회논문지C
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• 제35C권3호
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• pp.79-89
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• 1998

The Error Back-Propagation(EBP) algorithm is widely applied to train a multi-layer perceptron, which is a neural network model frequently used to solve complex problems such as pattern recognition, adaptive control, and global optimization. However, the EBP is basically a gradient descent method, which may get stuck in a local minimum, leading to failure in finding the globally optimal solution. Moreover, a multi-layer perceptron suffers from locking a systematic determination of the network structure appropriate for a given problem. It is usually the case to determine the number of hidden nodes by trial and error. In this paper, we propose a new algorithm to efficiently train a multi-layer perceptron. OUr algorithm uses stochastic perturbation in the weight space to effectively escape from local minima in multi-layer perceptron learning. Stochastic perturbation probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the EGP learning gets stuck to it. Addition of new hidden nodes also can be viewed asa special case of stochastic perturbation. Using stochastic perturbation we can solve the local minima problem and the network structure design in a unified way. The results of our experiments with several benchmark test problems including theparity problem, the two-spirals problem, andthe credit-screening data show that our algorithm is very efficient.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2010년도 하계학술대회 논문집
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• pp.258-258
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• 2010

In this work, back bias effects in the program of the silicon-oxide-nitride-oxide-silicon (SONOS) cell using two-step pulse sequence, are investigated. Two-step pulse sequence is composed of the forward biases for collecting the electrons at the substrate terminal and back bias for injecting the hot electrons into the nitride layer. With an aid of the back bias for electron injection, we obtain a program time as short as 600 ns and an ultra low-voltage operation with a substrate voltage of -3 V.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2011년도 제40회 동계학술대회 초록집
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• pp.394-394
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• 2011

최근 태양전지의 후면에서 통상적으로 사용되는 Al을 이용한 후면의 BSF형성과 그에 관한 연구보다 계면의 recombination을 줄이기 위하여 passivation 특성이 좋은 층을 후면에 형성하고 국부적으로 BSF를 형성하는 back contact을 형성하여 특성을 향상시키는 연구가 많이 이루어지고 있다. 본 연구는 이러한 local back contact을 boron-BSF를 이용하여 형성하고 passivation layer는 oxide를 이용한 구조를 SILVACO 2-dimension simulation을 이용하여 그 특성을 분석하였다. Boron-local back contact 구조에서 boron-BSF의 doping concentration, depth, lateral width, boron-BSF spacing 가변을 통해 태양전지의 특성변화에 대해서 spectrum response를 통한 QE 분석 및 I-V를 분석하여 최적화하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.415-418
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• 1995

This paper describes a new technique for thickness measurement of a very thin layer less than one-quarter of the wavelength of ultrasonic wave using ultrasonic pulse-echo method. The technique determines the thickness of a thin layer in a layered medium form the amplitudes of the total reflected waves from the back side layer of interst. Thickness of a very thin layer few inch deep inside the media can be measured without using a very high frequency ultrasonic transducer over 100MHz which must be used in the conventional techniques for the precision measurement of a thin layer. The method also requires no inversion process to extract the thickness from the waveform of the reflected waves, so that it makes possible on-line measurement of the thickness of the layer.

• 한국정보통신학회논문지
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• 제7권5호
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• pp.1044-1051
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• 2003

본 논문은 MLP의 학습 방법으로 사용되는 EBP학습, Cross Entropy함수, 계층별 학습을 소개하고, 필기체 숫자인식 문제를 대상으로 각 학습 방법의 장단점을 비교한다. 실험 결과, EBP학습은 학습 초기에 학습 속도가 다른 학습 방법에 비해 느리지만, 일반화 성능이 좋다. 또한, EBP학습의 단점을 보안한 Cross Entropy 함수는 학습 속도가 EBP학습보다 빠르다. 그러나, 출력층의 오차 신호가 목표 벡터에 대해 선형적으로 학습하기 때문에, 일반화 성능이 EBP학습보다 낮다. 그리고, 계층별 학습은 학습 초기에, 학습 속도가 가장 빠르다. 그러나, 일정한 시간 후, 더 이상 학습이 진행되지 않기 때문에, 일반화 성능이 가장 낮은 결과를 얻었다. 따라서, 본 논문은 MLP를 응용하고자 할 때, 학습 방법의 선택 기준을 제시한다.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2011년도 제41회 하계 정기 학술대회 초록집
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• pp.75-75
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• 2011

Recently, dye-sensitized solar cell (DSSC) attracts great attention as a promising alternative to conventional silicon solar cells. One of the key components for the DSSC would be the nanocrystalline TiO2 electrode, and the control of interface between TiO2 and TCO is a highly important issue in improving the photovoltaic conversion efficiency. In this work, we applied various interfacial layers, and analyzed their effect in enhancing photovoltaic properties. In overall, introduction of interfacial layers increased both the Voc and Jsc, since the back-reaction of electrons from TCO to electrolyte could be blocked. First, several metal oxides with different band gaps and positions were employed as interfacial layer. SnO2, TiO2, and ZrO2 nanoparticles in the size of 3-5 nm have been synthesized. Among them, the interfacial layer of SnO2, which has lower flat-band potential than that of TiO2, exhibited the best performance in increasing the photovoltaic efficiency of DSSC. Second, long-range ordered cubic mesoporous TiO2 films, prepared by using triblock copolymer-templated sol-gel method via evaporation-induced self-assembly (EISA) process, were utilized as an interfacial layer. Mesoporous TiO2 films seem to be one of the best interfacial layers, due to their additional effect, improving the adhesion to TCO and showing an anti-reflective effect. Third, we handled the issues related to the optimum thickness of interfacial layers. It was also found that in fabricating DSSC at low temperature, the role of interfacial layer turned out to be a lot more important. The self-assembled interfacial layer fabricated at room temperature leads to the efficient transport of photo-injected electrons from TiO2 to TCO, as well as blocking the back-reaction from TCO to I3-. As a result, fill factor (FF) was remarkably increased, as well as increase in Voc and Jsc.