• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.339-345
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• 1993

It is well known that distribution of functions of eigen values and vectors of a certain matrix plays an important role in multivariate analysis. This paper deals with the transformation of a correlation-type random matrix to its eigen values and vectors. Properties of the transformation are also considered. The results obtained are applied to express the joint distribution of eigen values and vectors of the correlation matrix when sample is taken from a m-variate spherical distribution.

• Journal of KSNVE
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• v.10 no.5
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• pp.800-805
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• 2000

To determine the modal matrix and modal frequency of engine mount system, we most solve so-called eigen-value problem. However eigen-value problem of engine mount system with hydraulic mount can not be solved by general eigne-analysis algorithm because the properties of hydraulic mount vary with frequency. so in this paper the method for modal analysis of rigid body motions of an engine supported by hydraulic mount is proposed. Natural frequencies and mode shapes of this nonlinear system are obtained by using complex exponential method and Laplace transformation method. In time domain, impulse response functions are calculated by (two-sided) discrete inverse Fourier Transformation of forced frequency response functions achieved by Laplace transformation of the differential equation of motion. Considering the fact that frequency response functions synthesized by modal parameters form proposed method are in good agreement with original FRFs, it is proved that the proposed method is very efficient and useful for the analysis of eigne-value problem of hydraulic engine mount system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.912-915
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• 2002

This paper presents off-line handwritten numeral recognition method by using Eigen-Vectors. In this method, numeral features are extracted statistically by using Eigen-Vectors through KL transform and input numeral is recognized in the feature space by the nearest-neighbor classifier. In our feature extraction method, basis vectors which express best the property of each numeral type within the extensive database of sample numeral images are calculated, and the numeral features are obtained by using this basis vectors. Through the experiments with the unconstrained handwritten numeral database of Concordia University, we have achieved a recognition rate of 96.2%.

• Proceedings of the KIEE Conference
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• 1998.11c
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• pp.1033-1036
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• 1998

In this research project, two aspects of small signal stability are studied: improvement in Hessenberg method to compute the dominant electromechanical oscillation modes and siting FACTS devices to damp the low frequency oscillation. Fourier transform of transient stability simulation results identifies the frequencies of the dominant oscillation modes accurately. Inverse transformation of the state matrix with complex shift equal to the angular speed determined by Fourier transform enhances the ability of Hessenberg method to compute the dominant modes with good selectivity and small size of Hessenberg matrix. Any specified convergence tolerance is achieved using the iterative scheme of Hessenberg method. Siting FACTS devices such as SVC, STACOM, TCSC, TCPR and UPFC has been studied using the eigen-sensitivity theory of augmented matrix. Application results of the improved Hessenberg method and eigen-sensitivity to New England 10-machine 39-bus and KEPCO systems are presented.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.685-688
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• 1998

In this research project, two aspects of small signal stability are studied: improvement in Hessenberg method to compute the dominant electromechanical oscillation modes and siting FACTS devices to damp the low frequency oscillation. Fourier transform of transient stability simulation results identifies the frequencies of the dominant oscillation modes accurately. Inverse transformation of the state matrix with complex shift equal to the angular speed determined by Fourier transform enhances the ability of Hessenberg method to compute the dominant modes with good selectivity and small size of Hessenberg matrix. Any specified convergence tolerance is achieved using the iterative scheme of Hessenberg method. Siting FACTS devices such as SVC, STACOM, TCSC, TCPR and UPFC has been studied using the eigen-sensitivity theory of augmented matrix. Application results of the improved Hessenberg method and eigen-sensitivity to New England 10-machine 39-bus and KEPCO systems are presented.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.365-368
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• 1998

In this research project two aspects of small signal stability are studied: improvement in Hessenberg method to compute the dominant electromechanical oscillation modes and siting FACTS devices to damp the low frequency oscillation. Fourier transform of transient stability simulation results identifies the frequencies of the dominant oscillation modes accurately. Inverse transformation of the state matrix with complex shift equal to the angular speed determined by Fourier transform enhances the ability of Hessenberg method to compute the dominant modes with good selectivity and small size of Hessenberg matrix. Any specified convergence tolerance is achieved using the iterative scheme of Hessenberg method. Siting FACTS devices such as SVC, STACOM, TCSC, TCPR and UPFC has been studied using the eigen-sensitivity theory of augmented matrix. Application results of the improved Hessenberg method and eigen-sensitivity to New England 10-machine 39-bus and KEPCO systems are presented.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.50 no.2
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• pp.195-206
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• 2017

Joint time-frequency images of the broadband echo signals of six fish species were obtained using the smoothed pseudo-Wigner-Ville distribution in controlled environments. Affine transformation and principal component analysis were used to obtain eigenimages that provided species-specific acoustic features for each of the six fish species. The echo images of an unknown fish species, acquired in real time and in a fully automated fashion, were identified by finding the smallest Euclidean or Mahalanobis distance between each combination of weight matrices of the test image of the fish species to be identified and of the eigenimage classes of each of six fish species in the training set. The experimental results showed that the Mahalanobis classifier performed better than the Euclidean classifier in identifying both single- and mixed-species groups of all species assessed.

• Bulletin of the Korean Mathematical Society
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• v.36 no.3
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• pp.467-476
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• 1999

In the present paper, we describe the action of isometry groups of 30dimensional weakly symmetric spaces and classify 3-dimensional connected weaky symmetric spaces. Further, we determine 3-dimensional weakly symmetric spaces in terms of the eigen- values of the Ricci transformation.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.55-64
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• 2000

We propose a criterion for testing homogeneity of matrix intraclass covariance matrices of K multivariate normal populations, It is based on a variable transformation intended to propose and develop a likelihood ratio criterion that makes use of properties of eigen structures of the matrix intraclass covariance matrices. The criterion then leads to a simple test that uses an asymptotic distribution obtained from Box's (1949) theorem for the general asymptotic expansion of random variables.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1745-1753
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• 2004

A method of estimating the pose of a three-dimensional object from a set of two-dimensioal images based on parametric eigenspace method is proposed. A Gaussian blurred edge image is used as an input image instead of the original image itself as has been used previously. The set of input images is compressed using K-L transformation. By comparing the estimation errors for the original, blurred original, edge, and blurred edge images, we show that blurring with the Gaussian function and the use of edge images enhance the data compression ratio and decrease the resulting from smoothing the trajectory in the parametric eigenspace, thereby allowing better pose estimation to be achieved than that obtainable using the original images as it is. The proposed method is shown to have improved efficiency, especially in cases with occlusion, position shift, and illumination variation. The results of the pose angle estimation show that the blurred edge image has the mean absolute errors of the pose angle in the measure of 4.09 degrees less for occlusion and 3.827 degrees less for position shift than that of the original image.