• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.566-570
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• 1986

본 논문의 목적은 대규모 선형 시불변 계통에 대한 합성 제어기의 설계에 관한 새로운 방법을 제시하기 위한 것이다. 주어진 계통을 행렬 부호 함수를 이용하여 그 고유치의 크기에 따라 블럭 대각 분해하고 각부 계통에 대한 최적 제어기 및 전체계통에 대한 준최적 합성 제어기를 설계한다. 이 방법은 주어진 계통의 고유치를 미리 알 필요가 없으며 계통의 블력 분해 과정에서 Riccati 방정식및 Lyapunov 방정식의 해를 구할 필요가 없고 특이섭등 기법이나 Two time scale seperation 방법에서의 제약조건에 관계없이 광범위하게 적용되는 장점이 있다.

• Investigative Magnetic Resonance Imaging
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• v.11 no.2
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• pp.110-118
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• 2007

Purpose: The objective of this work to construct eigenvalue maps that have information of magnitude of three primary diffusion directions using diffusion tensor images. Materials and Methods: To construct eigenvalue maps, we used a 3.0T MRI scanner. We also compared the Moore-Penrose pseudo-inverse matrix method and the SVD (single value decomposition) method to calculate magnitude of three primary diffusion directions. Eigenvalue maps were constructed by calculating of magnitude of three primary diffusion directions. We did investigate the relationship between eigenvalue maps and fractional anisotropy map. Results: Using Diffusion Tensor Images by diffusion tensor imaging sequence, we did construct eigenvalue maps of three primary diffusion directions. Comparison between eigenvalue maps and Fractional Anisotropy map shows what is difference of Fractional Anisotropy value in brain anatomy. Furthermore, through the simulation of variable eigenvalues, we confirmed changes of Fractional Anisotropy values by variable eigenvalues. And Fractional anisotropy was not determined by magnitude of each primary diffusion direction, but it was determined by combination of each primary diffusion direction. Conclusion: By construction of eigenvalue maps, we can confirm what is the reason of fractional anisotropy variation by measurement the magnitude of three primary diffusion directions on lesion of brain white matter, using eigenvalue maps and fractional anisotropy map.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.1641-1644
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• 2004

3차원 볼륨데이터에서 분할 대상영역의 밝기 값이 다양하면서 밝기 값이 유사한 영역과 인접한 경우 3차원 영역확장(region growing) 방법을 사용하여 영역을 분할하기 위해서는 영역확장의 중요한 요인인 동질성 기준 값의 적절한 선택이 요구된다. 본 논문에서는 영역 복셀(voxel)의 1차 미분 값의 크기인 기울기 크기(gradient magnitude)만으로 영역의 경계를 찾기가 쉽지않은 대상의 분할을 위해 볼륨데이터의 지역적인 밝기 값의 변화의 특징을 고려하면서 분할 대상영역의 복셀의 2차 미분(second partial derivation)을 행렬의 요소(element)로 갖는 Hessian 행렬의 고유치(eigenvalue)를 영역확장의 문턱치 결정에 이용하였다. 제안한 알고리즘은 3차원 영역확장의 결과에 가장 큰 영향을 미치는 적절한 문턱치의 선택으로 대상영역의 분할을 성공적으로 수행하여 3차원 영역확장의 단점을 보완하였다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.11
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• pp.813-818
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• 1987

In this paper, high resolution spectral estimation by AR modelling and principal comonent analysis is proposed. The given data can be expanded by the eigenvectors of the estimated covariance matrix. The eigenspectrum is obtained for each eigenvector using the Autoressive(AR) spectral estimation technique. The final spectrum estimate is obtained by weighting each eigenspectrum with the corresponding eigenvalue and summing them. Although the proposed method increases in computational complexity, it shows good frequency resolution especially for short data records and narrow-band data whose signal-to-noise ratio is low.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.414-416
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• 2012

본 논문에서는 X-선 혈관 조영 영상 내 심혈관의 추출 방법을 제안한다. 본 방법은 불균일 조명 보정 필터를 사용함으로써 X-선 영상 내에서 나타나는 일정하지 않은 contrast, 낮은 명암도 및 불균일 조명 문제를 해결한다. 또한 영상의 지역적인 밝기 값의 변화의 특징을 고려하면서 분할 대상영역의 각 픽셀들의 2 차 미분((second partial derivation)을 행렬의 요소(element)로 갖는 Hessian 행렬의 고유치 (eigenvalue)를 영역확장의 문턱치 결정에 이용하여 전역적인 밝기값(intensity)만을 사용하는 분할의 단점을보완하였다.

• The Journal of the Acoustical Society of Korea
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• v.32 no.6
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• pp.548-555
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• 2013

The localization of sources has a numerous number of applications. To estimate the position of sources, the relative delay between two or more received signals for the direct signal must be determined. Although the generalized cross-correlation method is the most popular technique, an approach based on eigenvalue decomposition (EVD) is also popular one, which utilizes an eigenvector of the minimum eigenvalue. The performance of the eigenvalue decomposition (EVD) based method degrades in the low SNR and the correlated environments, because it is difficult to select a single eigenvector for the minimum eigenvalue. In this paper, we propose a new adaptive algorithm based on Canonical Correlation Analysis (CCA) in order to extend the operation range to the lower SNR and the correlation environments. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue in the generalized eigenvalue decomposition (GEVD). The estimated eigenvector contains all the information that we need for time delay estimation. We have performed simulations with uncorrelated and correlated noise for several SNRs, showing that the CCA based algorithm can estimate the time delays more accurately than the adaptive EVD algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1013-1020
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• 2013

In this paper the super-resolution time delay estimation algorithms based on eigen-analysis are developed for spread spectrum signals along with their comparative performance analysis. First, we shall develop super-resolution time delay estimation algorithms using the representative eigen-analysis based AOA (angle-of-arrival) estimation algorithms such as MUSIC, Minimum-Norm, and ESPRIT, and apply them to the ISO/IEC 24730-2.1 real-time locating system (RTLS) employing a direct sequence spread spectrum (DS-SS) technique to compare their performances in RTLS environments. Simulation results illustrate that all the three algorithms can resolve multipath signals whose delay differences are even smaller than the Rayleigh resolution limit. Simulation results also show that MUSIC and Minimum-Norm provide a similar performance while ESPRIT is inferior to both algorithms in RTLS environments.

• The Journal of the Acoustical Society of Korea
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• v.26 no.3
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• pp.123-128
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• 2007

This Paper Presents new transient signal classification algorithms for underwater transient signals. In general. the ambient noise has small spectral deviation and energy variation. while a transient signal has large fluctuation. Hence to detect the transient signal, we use the spectral deviation and power variation. To classify the detected transient signal. the feature Parameters are obtained by using the Wigner-Ville distribution based eigenvalue decomposition. The correlation is then calculated between the feature vector of the detected signal and all the feature vectors of the reference templates frame-by-frame basis, and the detected transient signal is classified by the frame mapping rate among the class database.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.3B
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• pp.259-265
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• 2001

도래각 추정을 위한 대표적인 알고리즘으로 고유치 분해방식을 이용한 ESPRIT 알고리즘이 있다. 이 알고리즘은 다중 신호의 도래각을 추정할 수 있을 뿐만 아니라, 낮은 SNR에서 뛰어난 분해능을 가지고 있다. 이러한 뛰어난 추정 능력에도 불구하고, ESPRIT 알고리즘은 서로 주파수와 위상이 같은 coherent 한 신호를 분해하지 못하는 커다란 결점을 가지고 있다. 본 논문에서는 이러한 보완한 개선된 ESPRIT (Modified ESPRIT )알고리즘을 제안한다. 개선된 ESPRIT 알고리즘 기존의 ESPRIT 에 spatial smoothing 방법을 도입하여 구성되어진다. 모의실험결과 개선된 ESPRIT 알고리즘은 coherent 하게 입사하는 신호의 도래각을 분해하는 능력에 있어서 매우 우수한 성능을 갖고 있음을 확인할 수 있다.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.196-204
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• 2010

In this paper, we develope a defect inspection method for each buttons of keypad of cellular phones before they are assembled. The proposed algorithm consists of the similar color checking and its classification, font error detection, and scratch detection based on the segmentation of keypad area and font, translation and rotation processing sequentially. Especially, the proposed segmentation method approximate the pad region as B-spline function to deal with illumination change due to the shape of key button with the slant and curved surface followed by simple thresholding. And also, the rotational information is obtained by using eigen value and eigen vector very fast and effectively. The experimental results show that the performance of the proposed algorithm is good when it is applied to in-line process.