• Communications of the Korean Mathematical Society
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• v.32 no.3
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• pp.745-763
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• 2017

The Borel-Serre partial compactification gives cofinite models for the proper classifying space for arithmetic lattices. Non-arithmetic lattices arise only in semisimple Lie groups of ${\mathbb{R}}$-rank one. The author generalizes the Borel-Serre partial compactification to construct cofinite models for the proper classifying space for lattices in semisimple Lie groups of ${\mathbb{R}}$-rank one by using the reduction theory of Garland and Raghunathan.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.105-108
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• 1997

This paper proposes a new approach of balanced model reduction using matrix pencil. The algorithm presented in this paper is to convert full-rank high-order system into rank-deficient system using perturbation made by matrix pencil method. Then the system can be truncated to a low-order system that we want via balanced realization. We discuss the comparison with other methods and the various observations by simulations.

• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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• pp.123-126
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• 1992

A new class of data transformation matri is introduced for estimation of angles of arrivals by the rank reduction of multiple wideband sources. The proposed unitary focusing matri minimizes the average of the squared norm of focusing error over the angles of interest without a priori knowledge of source locations. The merit that result as a consequence is a lower resolution threshold. These matrices can be applied to the case of the multigroup sources. Simulations and the comparison of statistical performance are compared with the algorithms (especially, spatial resampling method) which does not require the pre-estimation.

• ETRI Journal
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• v.36 no.1
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• pp.167-170
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• 2014

In this letter, we propose an unsupervised framework for speech noise reduction based on the recent development of low-rank and sparse matrix decomposition. The proposed framework directly separates the speech signal from noisy speech by decomposing the noisy speech spectrogram into three submatrices: the noise structure matrix, the clean speech structure matrix, and the residual noise matrix. Evaluations on the Noisex-92 dataset show that the proposed method achieves a signal-to-distortion ratio approximately 2.48 dB and 3.23 dB higher than that of the robust principal component analysis method and the non-negative matrix factorization method, respectively, when the input SNR is -5 dB.

• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.26-30
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• 2009

We propose an adaptive Recursive Least Rank(RLR) L-filter which uses an L-estimator in order statistics and is based on rank estimate in robust statistics. The proposed RLR L-filter is a non-linear adaptive filter using non-linear adaptive algorithm and adapts itself to optimal filter in the sense of least dispersion measure of errors with non-homogeneous step size. Therefore the filter may be suitable for applications when the transmission channel is nonlinear channels such as Gaussian noise or impulsive noise, or when the signal is non-stationary such as image signal.

• Information and Communications Magazine
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• v.31 no.11
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• pp.35-45
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• 2014

주성분 분석 기법(PCA)는 가장 널리 사용되는 데이터 차원 감소 (dimensionality reduction) 기법으로 알려져 있다. 하지만 데이터에 이상점 (outlier)가 존재하는 환경에서는 성능이 크게 저하된다는 단점을 가지고 있다. Rank-Sparsity(Robust PCA) 기법은 주어진 행렬을 low-rank 행렬과 저밀도(sparse)행렬의 합으로 분해하는 방식으로, 이상점이 많은 환경에서 PCA기법을 효과적으로 대체할 수 있는 알고리즘으로 알려져 있다. 본 고에서는 RPCA 기법을 간략히 소개하고, 그의 적용분야, 및 알고리즘에 관한 연구들을 대해서 알아본다.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.129-135
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• 2011

An algorithm is presented for estimating the 3-D location (i.e., azimuth angle, elevation angle, and range) of multiple sources with a uniform circular array (UCA) consisting of an even number of sensors. Recently the rank reduction (RARE) algorithm for partly-calibrated sensor arrays was developed. This algorithm is applicable to sensor arrays consisting of several identically oriented and calibrated linear subarrays. Assuming that a UCA consists of M sensors, it can be divided into M/2 identical linear subarrays composed of two facing sensors. Based on the structure of the subarrays, the steering vectors are decomposed into two parts: range-independent 2-D direction-of-arrival (DOA) parameters, and range-relevant 3-D location parameters. Using this property we can estimate range-independent 2-D DOAs by using the RARE algorithm. Once the 2-D DOAs are available, range estimation can be obtained for each source by defining the 1-D MUSIC spectrum. Despite its low computational complexity, the proposed algorithm can provide an estimation performance almost comparable to that of the 3-D MUSIC benchmark estimator.

• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.105-122
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• 2012

This paper proposes a fuzzy-based AHP model by which the greenhouse gas reduction for container terminal problem was systematically structured and then evaluated. The model was established by exploiting a fuzzy theory and AHP for capturing the inexactness and vagueness of information. In this study, measurement areas were selected for equipment aspect, operating aspect, and energy aspect. The greenhouse gas reduction is the number one priority in the equipment aspect, operating aspect, energy aspect in order. The analysis result of equipment aspect reveals that the most important element is electrical T/C. The most important element of operating and energy aspect were a container rehandling and a LED lighting. As for the whole priority which conversion weight was applied, the results were shown as follows: an electrical T/C(16.2%) as the first rank: a hybrid Y/T(14.4%) as the second rank: a AMP(10.6%) as the third rank. The result of this study suggests some guidelines for deciding priority of greenhouse gas reduction for container terminal.

• Communications of the Korean Mathematical Society
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• v.30 no.2
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• pp.65-72
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• 2015

The minimum rank mr(G) of a simple graph G is defined to be the smallest possible rank over all symmetric real matrices whose (i, j)-th entry (for $i{\neq}j$) is nonzero whenever {i, j} is an edge in G and is zero otherwise. The corona $C_n{\circ}K_t$ is obtained by joining all the vertices of the complete graph $K_t$ to each n vertex of the cycle $C_n$. For any t, we obtain an upper bound of zero forcing number of $L(C_n{\circ}K_t)$, the line graph of $C_n{\circ}K_t$, and get some bounds of $mr(L(C_n{\circ}K_t))$. Specially for t = 1, 2, we have calculated $mr(L(C_n{\circ}K_t))$ by the cut-vertex reduction method.

• Korean Journal of Health Education and Promotion
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• v.30 no.5
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• pp.201-210
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• 2013

Objectives: The public relies on the news media to understand health risks. To examine the surveillance function of Korean health journalism, this study compared the rank-order of the 10 most frequently diagnosed cancers with that of the 10 cancers most frequently covered by three major Korean newspapers. Methods: News stories published between 1999 and 2010 by the Chosun-Ilbo, Joong-Ang-Ilbo, and Dong-A-Ilbo were examined. Data on cancer incidence were collected using the epidemiological data published by a governmental public health institution. To compare the level of the crude rates and the amount of news coverage, rank-order correlation tests and regression analyses were employed. Results: A reduction in the rank-ordered correlation coefficient was observed despite an increase in the overall number of cancer news stories released. The significance of the correlation disappeared after 2006. The big difference of the rank order between the crude rate and the amount of news coverage was observed in the cancer of breast, uteri, thyroid, and gallbladder/biliary. Finally, the three newspapers did not follow the amount change in stomach, lung, liver, and uterine cervix cancer. The four cancers' rank orders of crude rate were lowering, signifying a reduction of the comparative dangerousness of the four cancers. Conclusions: The news media's customization of news content and the negative bias in journalism are suggested as possible influences on the news media's inaccurate representation of cancer risk.