• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2217-2222
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• 2011

In this paper, the relationship of potential and charge distribution in channel for double gate(DG) MOSFET has been derived from Poisson's equation using Gaussian function. The relationship of subthreshold swing and oxide thickness has been investigated according to variables of doping distribution using Gaussian function, i.e. projected range and standard projected deviation, The analytical potential distribution model has been derived from Poisson's equation, and subthreshold swing has been obtained from this model for the change of oxide thickness. The subthreshold swing has been defined as the derivative of gate voltage to drain current and is theoretically minimum of 60 mS/dec, and very important factor in digital application. Those results of this potential model are compared with those of numerical simulation to verify this model. As a result, since potential model presented in this paper is good agreement with numerical model, the relationship of subthreshold swing and oxide thickness have been analyzed according to the shape of doping distribution.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.1
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• pp.1-8
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• 2001

본 논문에서는 정규화된 데이터 공간과 가우스함수에 의한 산 함수 형성 그리고 형성된 산의 기울기를 이용한 산봉우리 붕괴를 특징으로 하는 개선된 산 클러스터링 방법을 제안한다. 이 개선된 방법은 기존의 Yager 등에 의하여 제안된 방법이 조정해야 하는 매개변수가 3개이고 발견된 클러스터 중심 주위에 원치 않는 다른 중심이 발생할 수 있는데 반하여 단지 하나의 매개변수 $\omega$의 조정으로 더욱 타당한 중심을 찾아내는 점에서 유용하다 할 수 있다. 또한 매개변수 $\omega$에 대한 적절한 선정 방법을 제시하고, 수치 자료에 대한 컴퓨터 모의실험을 통하여 개선된 산 클러스터링 방법의 유용성을 입증한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.57-63
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• 2008

In this paper, we present an efficient noise reduction method using bivariate Gaussian density function in the wavelet domain. In our method, the probability model for the interstate dependency in the wavelet domain is modeled by bivariate Gaussian function, and then, the noise reduction is performed by Bayesian estimation. The statistical parameter for Bayesian estimation can be approximately obtained by the $H{\ddot{o}}lder$ inequality. The simulation results show that our method outperforms the previous methods using bivariate probability models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.3
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• pp.263-279
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• 1989

In part-1 of this paper, the error rate equations of digitally modulated signals transmitted though the Gaussian/Impulsive noise channel have been derived. Using the derived equations for the error probabilities of ASK, QAM, CPSK, DPSK, FSK and MSK signals, the error rate performances of digital modulation systems have been evaluated and represented in the figures as the functions of carrier-to-noise power ratio(CNR), impulsive index, and the ration of Gaussian noise power component to impulsive noise power component. The results are shown in graphs to known how much impulsive noise effects on digital signals than Gaussian noise.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.136-141
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• 1994

In this paper, we implemented an opto-electronical signal processing system for the edge detection using the diffusion neural network. The diffusion neural network performs a Gaussian and DOG operation efficiently by the diffusion process. The diffusion neural network is more efficient than the LOG masking method in hardware implementation because it has a few connections and the connection weights are fixed-valued. We implemented a diffusion neural network using the characteristics of the light intensity distribution function which is similar to the Gaussian function. We have shown that the system can detect the edge of an image exactly through the experimental results.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.1-10
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• 2020

Effective jamming in electronic warfare depends on proper jamming technique selection and jamming parameter estimation. For this purpose, this paper proposes a new method of estimating jamming parameters using Gaussian kernel function networks. In the proposed approach, a new method of determining the optimal structure and parameters of Gaussian kernel function networks is proposed. As a result, the proposed approach estimates the jamming parameters in a reliable manner and outperforms other methods such as the DNN(Deep Neural Network) and SVM(Support Vector Machine) estimation models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.570-578
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• 2007

선체 외판 부재의 곡 성형 과정은 주로 가열(열간가공)에 의해 수행된다. 이 가열 작업은 작업자의 경험과 지식에 크게 의존하는 매우 어려운 작업이다. 본 논문에서는 선체 외판의 곡 성형을 위한 가열 계획을 자동으로 수립할 수 있는 휴리스틱을 소개한다. 현장 전문가의 지식에 기반한 이 휴리스틱은 크게 가열 선을 생성하는 부분과 외력을 주는 도구를 배치하는 부분으로 구성된다. 가열 선은 대상 부재의 현재 곡면과 설계된 목적곡면과의 비교를 통해 생성되고, 가우스 커널 함수를 통해 스무딩(smoothing)된다. 현장에서는 열간가공 시 의도하지 않은 변형을 막으면서 작업시간을 줄이고자 외력을 이용한다. 외력의 위치와 방향은 가열 선 군집화를 통해 추출된 대표 가열 선을 기준으로 결정된다. 가상의 인공 곡면과 현장의 실제 부재를 대상으로 실험한 결과, 이 휴리스틱이 숙련된 전문가가 수립한 가열 계획과 유사한 가열 계획을 수립할 수 있음을 확인하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.157-158
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• 2019

발전소 관리의 단기 전력 수요에 대한 정확한 예측은 전력 시스템의 안전하고 효율적인 작동을 보장하는데 필수적이다. 따라서 본 연구는 가우스 커널 함수 네트워크 (GKFNs)의 심층 구조를 이용하여 일일 최대 전력 수요를 예측하는 새로운 방법을 제시한다. 제안 된 GKFN의 깊이 구조는 표준 GKFN에 비해 예측 정확도를 향상시킨다. 한국의 일일 최대 전력 수요를 예측하기위한 시뮬레이션은 제안 된 예측 모델이 GKFN 모델, k-NN 및 SVR과 같은 다른 예측 모델에 비해 예측 성능에 이점이 있음을 보여준다. GKFN의 제안된 심층 구조는 시계열 예측 및 회귀 문제의 다양한 문제에 적용될 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.651-656
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• 2014

This paper analyzed the change of subthreshold swing for channel doping of asymmetric double gate(DG) MOSFET. The subthreshold swing is the factor to describe the decreasing rate of off current in the subthreshold region, and plays a very important role in application of digital circuits. Poisson's equation was used to analyze the subthreshold swing for asymmetric DGMOSFET. Asymmetric DGMOSFET could be fabricated with the different top and bottom gate oxide thickness and bias voltage unlike symmetric DGMOSFET. It is investigated in this paper how the doping in channel, gate oxide thickness and gate bias voltages for asymmetric DGMOSFET influenced on subthreshold swing. Gaussian function had been used as doping distribution in solving the Poisson's equation, and the change of subthreshold swing was observed for projected range and standard projected deviation used as parameters of Gaussian distribution. Resultly, the subthreshold swing was greatly changed for doping concentration and profiles, and gate oxide thickness and bias voltage had a big impact on subthreshold swing.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.241-256
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• 2006

We generalize the $Cram{\acute{e}}r$-von Mises Statistic to test multivariate normality using Roy's union-intersection principle. We show the limit distribution of the suggested statistic is representable as the integral of a suitable Gaussian process. We also consider the computational aspects of the proposed statistic. Power performance is assessed in a Monte Carlo study.