• The Journal of the Acoustical Society of Korea
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• v.13 no.2
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• pp.76-85
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• 1994

A speech enhancement algorithm which attenuates nonstationary colored noise is presented In this paper. The algorithm consists of a stationary Kalman filter and the simple speech/nonspeech detector. While the conventional enhancement systems are focused on a stationary and/or white background noise, this study Is focused on the mort realistic nonstationary and nonwhite noise. An AR model-based vector Kalman filter is used as a noise suppression system and a short-time energy threshold logic is used as a speech/nonspeech classifier. For Kalman filtering. noise coefficients are estimated in the nonspeech frame, and speech coefficients are estimated by applying the EM iteration algorithm. Simulation results using the car noise are presented based on the signal-to-noise ratio and informal listening tests. According to the experimental results, background noises in the nonspeech frames are eliminated almost completely, while some distortions are noticed in the speech frames. The distortion becomes severer as the SNR is reduced to 0dB and -5dB. Intelligibility, however, is not degraded significantly.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.540-547
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• 2004

Since speech enhancement algorithms based on Kalman/Wiener filter require a priori knowledge of the noise and have focused on the minimization of the variance of the estimation error between clean and estimated speech signal, small estimation error on the noise statistics may lead to large estimation error. However, H/sub ∞/ filter does not require any assumptions and a priori knowledge of the noise statistics, but searches the best estimated signal among the entire estimated signal by applying least upper bound, consequently it is more robust to the variation of noise statistics than Kalman/Wiener filter. In this paper, we Propose a speech enhancement method using HMM and multi H/sub ∞/ filters. First, HMM parameters are estimated with the training data. Secondly, speech is filtered with multiple number of H/sub ∞/ filters. Finally, the estimation of clean speech is obtained from the sum of the weighted filtered outputs. Experimental results shows about 1dB∼2dB SNR improvement with a slight increment of computation compared with the Kalman filter method.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.847-858
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• 2015

Deep-sea fishery in the Antarctic Ocean has been actively progressed by the developed countries including Korea. In order to prevent the environmental destruction of the Antarctic Ocean, related countries have established the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and have monitored any illegal unreported or unregulated fishing. Fishing of tooth fish, an expensive fish, in the Antarctic Ocean has increased recently and high catches per unit effort (CPUE) of fishing boats, which is suspicious for an illegal activity, have been frequently reported. The data of CPUEs in a fishing area of the Antarctic Ocean often show an extreme Distribution or a mixture of two extreme distributions. This paper proposes an algorithm to detect an outlier of CPUEs by using the mixture of two extreme distributions. The parameters of the mixture distribution are estimated by the EM algorithm. Log likelihood value and posterior probabilities are used to detect an outlier. Experiments show that the proposed algorithm to detect outlier of the data can be adopted instead of simple criteria such as a CPUE is greater than 1.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.721-727
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• 2016

In this paper, in order to resolve the problem of reduction for D2D (device to device) advertisement dissemination efficiency of conventional dissemination algorithms, we here propose several clustering algorithms (modified single linkage algorithm (MSL), K-means algorithm, and expectation maximization algorithm with Gaussian mixture model (EM)) based advertisement dissemination algorithms to improve advertisement dissemination efficiency in D2D communication networks. Target areas are clustered in several target groups by the proposed clustering algorithms. Then, D2D advertisements are consecutively distributed by using a routing algorithm based on the geographical distribution of the target areas and a relay selection algorithm based on the distance between D2D sender and D2D receiver. Via intensive MATLAB simulations, we analyze the performance excellency of the proposed algorithms with respect to maximum number of relay transmissions and D2D user density ratio in a target area and a non-target area.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.126-128
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• 2010

지형 참조 항법(TRN, Terrain reference navigation)은 항체에 탑재된 지형 데이터베이스와 센서로부터 측정된 고도값을 대조하여 항체의 위치를 알아내는 것으로, GPS/INS 결합항법 시스템의 대체 항법으로 많이 알려져 있다. 지형의 형태에 따라서 시스템의 정확도와 안정성이 달라지기 때문에 특정적인 지형 정보를 이용하여 지형 데이터베이스와 대조하는 과정이 매우 중요하다. 따라서 본 논문에서는 센서 측정값과 지형 데이터베이스 상의 값에서 지형의 특성적 변화가 발생하는 지점인 Model Key Point를 2D Douglas-Peucker 알고리즘을 이용하여 추출하고 이를 항법 알고리즘에 적용하여 시뮬레이션 하였다. 그 결과 오차가 발산하지 않고 수십m 급의 항법 정밀도를 얻을 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.263-266
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• 2007

This paper discusses the Bayesian statistical inference. This paper discusses the Bayesian inference, MCMC (Markov Chain Monte Carlo) integration, MCMC method, Metropolis-Hastings algorithm, Gibbs sampling, Maximum likelihood estimation, Expectation Maximization algorithm, missing data processing, and BMA (Bayesian Model Averaging). The Bayesian statistical inference is used to process a large amount of data in the areas of biology, medicine, bioengineering, science and engineering, and general data analysis and processing, and provides the important method to draw the optimal inference result. Lastly, this paper discusses the method of principal component analysis. The PCA method is also used for data analysis and inference.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.745-747
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• 2004

소실점은 실 공간의 평행한 직선들이 영상에서 만나는 점으로서 카메라 파라미터 추정. 영상을 사용한 3차원 구조복원 등에서 널리 사용되는 영상 상에 존재하는 3차원 기하에 대한 암묵적인 특징 정보이다. 본 논문에서는 영상으로부터 안정적으로 소실점을 검출하기 위한 새로운 방법을 제시한다. 먼저 단위구 상에서 셀 기반의 소실 공간을 EM 알고리즘의 초기 소실점으로 사용함한 신뢰성 있는 소실점 추출 방법을 제안한다. 또한 단일 영상에서 제거되지 않는 이상치에 대해 다중 영상에서 H응 직선이 가자는 사영불변치인 planar collineation과 harmonic range를 이용하여 보다 정확한 소실점을 구하기 위한 방법을 제안한다. 본 논문에서 제안한 알고리즘을 다양한 영상을 통해 실험한 결과 안정적이고 신뢰할만한 소실점 검출이 가능하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12C
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• pp.1200-1208
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• 2003

Affective computing plays an important role in intelligent Human Computer Interactions(HCI). To detect emotional events, it is desirable to construct a computing model for extracting emotion related features from video. In this paper, we propose a statistical model based on the probabilistic distribution of low level features in video shots. The proposed method extracts low level features from video shots and then from a GMM(Gaussian Mixture Model) for them to detect emotional shots. As low level features, we use color, camera motion and sequence of shot lengths. The features can be modeled as a GMM by using EM(Expectation Maximization) algorithm and the relations between time and emotions are estimated by MLE(Maximum Likelihood Estimation). Finally, the two statistical models are combined together using Bayesian framework to detect emotional events in video.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.87-93
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• 2017

A maximum likelihood (ML) approach is presented for estimating the mean of radar cross section (RCS) of a Swerling III target and its numerical solution methods are discussed. The solution methods are based on an approximate expression for implementing the expectation maximization (EM) algorithm. The methods are evaluated and compared through Monte Carlo simulations in terms of estimation accuracy and computational efficiency to obtain a most efficient method for both Swerling I and Swerling III targets. The methods are also compared with a previously reported method based on heuristics.

• Annual Conference on Human and Language Technology
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• 2007.10a
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• pp.233-240
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• 2007

온톨로지 구축에서 클래스간 관계 설정은 중요한 부분이다. 본 논문에서는 클래스간 상 하위 관계 외의 관계 설정을 위한 클래스간 관계 자동 정의를 목적으로 의존구문분석의 (주어, 용언) (목적어, 용언) 쌍들을 추출하고, 이렇게 추출된 데이터를 이용하여 용언들을 클러스터링 하는 방법을 제안한다. 도메인 전문 코퍼스 데이터 희귀성 문제를 해결하고자, 웹검색을 결합한 방식을 선택하여 도메인 온톨로지 구축 클래스간 관계 자동 설정에 대한 방법론을 제시한다.