• Wind and Structures
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• v.7 no.6
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• pp.359-372
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• 2004

Wind tunnel model studies were carried out to determine the wind load distribution on tributary areas near the gable-end of large, low-rise buildings with high pitch planar and curved roof shapes. Background pressure fluctuations on each tributary area are described by a series of uncorrelated modes given by the eigenvectors of the force covariance matrix. Analysis of eigenvalues shows that the dominant first mode contributes around 40% to the fluctuating pressures, and the eigenvector mode-shape generally follows the mean pressure distribution. The first mode contributes significantly to the fluctuating load effect, when its influence line is similar to the mode-shape. For such cases, the effective static pressure distribution closely follows the mean pressure distribution on the tributary area, and the quasi-static method would provide a good estimate of peak load effects.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06b
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• pp.97-102
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• 1999

멀티미디어 데이터의 증가로 사용자가 원하는 데이터의 신속하고 정확한 검색이 필요하게 되었다. 본 논문에서는 모양 정보를 기반으로 영상 데이터를 효과적이며 효율적으로 검색하기 위하여, 새로운 모양 정보 특징 및 검색 방법을 제안한다. 본 논문에서는 화소의 공간적분포로 나타나는 모양 정보를 covariance matrix의 eigenvector를 이용하여, 계층적으로 영역을 분할하고, 각 분할된 영역에서 크기 변화, 위치 이동, 회전에 불변하는 특징들을 추출한다. 영상 정보의 검색은 특징벡터 공간에서 질의 영상에서 추출된 특징과, 데이터베이스에 기록된 영상들의 특징 사이의 거리를 계산하여, 거리에 반비례하는 유사도가 높은 영상들을 출력한다. 제안된 모양 특징은 또한 계층수의 조정에 의해서 모양 정보를 표현할 수 있는 정도를 조절 할 수 있다는 장점이 있다.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.531-541
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• 2012

In this study, we consider various methods to estimate the weights of a pairwise comparison matrix in the Analytic Hierarchy Process widely applied in various decision-making fields. This paper uses a data dependent simulation to evaluate the statistical accuracy, minimum violation and minimum norm of the obtaining weight methods from a reciprocal symmetric matrix. No method dominates others in all criteria. Least squares methods perform best in point of mean squared errors; however, the eigenvectors method has an advantage in the minimum norm.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.21-26
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• 2003

The well-conditioned observer in a stochastic system is designed so that the observer is less sensitive to the ill-conditioning factors in transient and steady-state observer performance. These factors include not only deterministic issues such as unknown initial estimation error, round-off error, modeling error and sensing bias, but also stochastic issues such as disturbance and sensor noise. In deterministic perspectives, a small value in the L$_2$ norm condition number of the observer eigenvector matrix guarantees robust estimation performance to the deterministic issues and its upper bound can be minimized by reducing the observer gain and increasing the decay rate. Both deterministic and stochastic issues are considered as a weighted sum with a LMI (Linear Matrix Inequality) formulation. The gain in the well-conditioned observer is optimally chosen by the optimization technique. Simulation examples are given to evaluate the estimation performance of the proposed observer.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.453-456
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• 1992

A Data-based Covariance Matrix(DCM) is introduced in the Eigenvector(EV) method, among subspace methods of estimating multiple sinusoidal frequencies from finite white noisy measurements. It is shown that the EV with the DCM can obtain the true. frequencies from finite noiseless data Some asymptotic results and further improvement on the DCM are also presented mathematically. Monte-carlo simulations are statistically conducted from the view-points of means and standard deviations in the EV's of DCM and Conventional Covariance Matrix(CCM). Simulations show a great promise for using the DCM, particularly for the cases of short data records, closely spaced frequencies and high signal-to-noise ratios.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.44.5-44
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• 2002

We propose a concept of the S-eigenvalue(stochastic-eigenvalue) along with corresponding eigenvector, and then we define the PDF corresponding to the S-eigenvalue on a complex plane. Based on the S-eigenvalue concept, we will establish the S-stability concept for linear continuous-time systems with probabilistic uncertainties in the system matrix. These results explicitly characterize how the S-eigenvalue in the complex plane may impose S-stability on S-eigenstructure assignment. Finally, we present numerical examples to illustrate the proposed concept.

• The Pure and Applied Mathematics
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• v.18 no.3
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• pp.185-199
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• 2011

In this paper, we present a new extended Jacobi method for computing eigenvalues and eigenvectors of Hermitian matrices which does not use any complex arithmetics. This method can be readily applied to skew-Hermitian and real skew-symmetric matrices as well. An example illustrating its computational efficiency is given.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.2
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• pp.59-70
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• 1996

Given the flow matrix, plant size (rectangle shape) and department sizes, the algorithm in this paper provides the plant layout with rectilinear distance measure. To construct automated facility design, eigenvector approach is employed. A branch and bound computer code developed by Tillinghast is modified to find the feasible fits of departments without shape distortion (see [1])in the plant rectangle. The computational results compared with CRAFT are shown.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.10a
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• pp.28-31
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• 1997

Buckling analysis of thin compressed beam has been carried out. Pre-buckling and post-buckling are simulated by finite element method incorporating with the incremental nonlinear theory and the Newton-Raphson solution technique. In order to find the bifurcation point, the determinent of the stiffness matrix is calculated at every iteration procedure. For post-buckling analysis, a small perturbed initial guess is given along the eigenvector direction at the bifurcation point. Nonlinear elastic buckling and elastic-plastic buckling of cantilever beam are analyzed. The buckling load and buckled shape of the two models are compared.

• Kyungpook Mathematical Journal
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• v.57 no.2
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• pp.211-222
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• 2017

In this paper, we consider three inverse eigenvalue problems for a special type of acyclic matrices. The acyclic matrices considered in this paper are described by a graph called a broom on n + m vertices, which is obtained by joining m pendant edges to one of the terminal vertices of a path on n vertices. The problems require the reconstruction of such a matrix from given partial eigen data. The eigen data for the first problem consists of the largest eigenvalue of each of the leading principal submatrices of the required matrix, while for the second problem it consists of an eigenvalue of each of its trailing principal submatrices. The third problem has an eigenvalue and a corresponding eigenvector of the required matrix as the eigen data. The method of solution involves the use of recurrence relations among the leading/trailing principal minors of ${\lambda}I-A$, where A is the required matrix. We derive the necessary and sufficient conditions for the solutions of these problems. The constructive nature of the proofs also provides the algorithms for computing the required entries of the matrix. We also provide some numerical examples to show the applicability of our results.