• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.295-297
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• 2006

본 논문에서는 연속 영상에서 가우시안 분포를 사용하여 사람의 얼굴을 추적하는 방법을 제안한다. 영상은 여러 개의 동질한 영역들로 이루어지고, 이 영역들 중 얼굴 영역이 있다고 가정하였다. 영상에 있는 모든 영역들을 가우시안 분포로 표현하였으며, 이들의 집합을 가우시안 분포의 혼합 모델로 표현하였다. 제안된 방범에서는 이전 프레임에서 가우시안 분포들을 찾고, 찾아진 이전 프레임의 가우시안 분포들을 이용하여 현재 프레임의 영역들을 찾는다. 이 영역들 중, 초기에 주어진 얼굴 영역이 있으며 현재 프레임의 영역들에 의해 가우시안 분포는 갱신되고 이 과정을 반복함으로써 얼굴을 추적한다. 가우시안 분포의 개수를 다양하게 변화시켜 실험을 하였고, 이를 통해 가우시안 분포의 혼합 모델로 얼굴을 추적할 수 있음을 보였다.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.203-213
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• 2017

We study estimation and inference of joint conditional distributions of bivariate longitudinal outcomes using regression models and copulas. We consider a class of time-varying transformation models and combine the two marginal models using Gaussian copulas to estimate the joint models. Our models and estimation method can be applied in many situations where the conditional mean-based models are inadequate. Gaussian copulas combined with time-varying transformation models may allow convenient and easy-to-interpret modeling for the joint conditional distributions for bivariate longitudinal data. We apply our method to an epidemiological study of repeatedly measured bivariate cholesterol data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.3
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• pp.130-134
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• 1985

In two-dimensional discrete cosine transform(DCT) coding, the measurements of the distributions of the transform coefficients are important because a better approximation yields a smaller mean square distorition. This paper presents the results of distribution tests which indicate that the statistics of the AC coefficients are well approximated to a generalized Gaussian distribution whose shape parameter is 0.6. Furthermore, from a simulation of the DCT coding, it was shown that the above approximation yields a higher experimental SNR and a better agreement between theory and simulation than the Gaussian or Laplacian assumptions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1409-1413
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• 2013

This paper analyzed the change of subthreshold current for channel doping concentration of double gate(DG) MOSFET. Poisson's equation had been used to analyze the potential distribution in channel, and Gaussian function had been used as carrier distribution. The potential distribution was obtained as the analytical function of channel dimension, using the boundary condition. The subthreshold current had been analyzed for channel doping concentration, and projected range and standard projected deviation of Gaussian function. Since this analytical potential model was verified in the previous papers, we used this model to analyze the subthreshold current. As a result, we know the subthreshold current was influenced on parameters of Gaussian function and channel doping concentration for DGMOSFET.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.17-20
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• 2003

본 논문에서는 공유 모델링의 대표적인 방법인 결정트리 기반 상태공유 모델을 기반으로 하여 그 출력 확률 분포의 혼합 가우시안 수를 줄임으로써 모델을 최적화하고자 하였다. 결정트리 기반의 상태공유 모델링은 일반적인 방법을 따랐으며 혼합 가우시안 수를 늘려 인식률이 최대가 되는 지점에서 혼합 가우시안을 클러스터링하여 그 수를 줄였다. 클러스터링 시에 필요한 거리 측정 방법이나 가까운 두 가우시안의 합성 방법을 여러 기법을 실험하였다. 이때 인식률은 클러스터링 이전인 97.2%를 유지하였으며 총 혼합 가우시안의 감소율은 1.0%를 보임으로써 모델을 최적화할 수 있었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.46-46
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• 2017

지역가뭄빈도분석의 분위산정에 대한 신뢰성은 수문학적으로 균일한 지역으로 구분하기 위해 사용된 장기간의 과거 자료와 분석절차에 의해 결정된다. 그러나 극심한 가뭄은 매우 드물게 발생하며 신뢰 할 수 있는 지역빈도분석을 위한 지속기간이 충분치 않는 경우가 많이 발생한다. 이 외에도 우리나라의 복잡한 지형적 및 기후적 특징은 동질한 지역으로 구분하기 위한 통계적인 처리방법이 필요하였다. 본 연구에서 적용한 지역빈도분석은 여러 지역의 다양한 변수인 수문기상 특성을 분석하여 동질한 지역을 확인하고, 주요 가뭄변수(지속 시간 및 심각도)를 통합 적용하여 각각의 동질한 지역 분위를 추정함으로써 동질한 지역을 구분하는 해결책을 제시하였다. 본 연구에서는 가우시안 혼합 모형(Gaussian Mixture Model)을 기반으로 기반 군집분석 방법을 적용하여 최적의 동질한 지역을 구분하고 그 결과를 우도비검정 및 다른 유효성 검사 지수를 이용해서 확인하였다. 가우시안 혼합 모델에서 산정했던 매개변수를 방향저감 공간으로 표현하기 위해서 가우시안 혼합 모델방향 저감(GMMDR)방법을 적용하였다. 이 변수는 가뭄빈도분석을 위해 다양한 분포와 코풀라(copula) 적합도를 이용하여 추정 비교하였다. 그 결과 우리나라를 4개의 동질한 지역으로 나누게 되었다. 가우시안과 Frank copula를 이용한 Pearson type III(PE3) 분포는 우리나라의 가뭄 기간과 심각도의 공동 분포를 추정하는데 적합한 것으로 나타났다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.125-132
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• 2010

In vocabulary recognition has unseen tri-phone appeared when recognition training. This system has not been created beginning estimation figure of model parameter. It's bad points could not be created that model for phoneme data. Therefore it's could not be secured accuracy of Gaussian model. To improve suggested Gaussian model to optimized method of model parameter using probability distribution. To improved of confidence that Gaussian model to optimized of probability distribution to offer by accuracy and to support searching of phoneme data. This paper suggested system performance comparison as a result of recognition improve represent 1.7% by out-of vocabulary rejection algorithm using normalization confidence.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.725-730
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• 2007

Gray-level histogram-based threshold selection methods such as Otsu's method, Huang and Wang's method, and etc. have been widely used for the threshold selection in image processing. They are simple and effective, but take too much time to determine the optimal multilevel threshold values as the number of thresholds are increased. In this paper, we measure correlation between gray-levels by using the Gaussian function and define a Gaussian-type finite mixture distribution which is combination of the Gaussian distribution function with the gray-level histogram, and propose a fast and effective threshold selection method using it. We show the effectiveness of the proposed through experimental results applied it to three images and the efficiency though comparison of the computational complexity of the proposed with that of Otsu's method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.99-104
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• 2000

In this paper, as a digital watermark we propose to use a chaotic sequence instead of the conventional Gaussian sequence. It is relatively easy to generate the chaotic sequence and is very sensitive to the change of initial value. The chaotic sequence adopted in this paper is a modified version of logistic map to give the sequence distribution of Chebyshev map. In the experiments, we applied the Gaussian sequence and chaotic sequence to wavelet coefficients of images to compare the similarity distribution. The results show that, as id the DCT-based watermarking system, the chaotic sequence is robust for various signal processing attacks, Moreover, the similarity variance is smaller than the Gaussian sequence for iterative experiments. It also shows a better performance for compression errors than the Gaussian sequence.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.127-134
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• 2010

In continuous vocabulary recognition system by probability distribution of clustering method has used model parameters of an advance estimate to generated each contexts for phoneme data surely needed but it has it's bad points of gaussian model the accuracy unsecure of composed model for phoneme data. To improve suggested probability distribution mixed gaussian model to optimized that phoneme data search supported configuration thread system. This paper of configuration thread system has used extension facet classification user phoneme configuration thread information offered gaussian model the accuracy secure. System performance as a result of represent vocabulary dependence recognition rate of 98.31%, vocabulary independence recognition rate of 97.63%.