• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.471-479
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• 2008

Let $R\;{\in}\;C^{m{\times}m}$ and $S\;{\in}\;C^{n{\times}n}$ be nontrivial unitary involutions, i.e., $R^*\;=\;R\;=\;R^{-1}\;{\neq}\;I_m$ and $S^*\;=\;S\;=\;S^{-1}\;{\neq}\;I_m$. We say that $G\;{\in}\;C^{m{\times}n}$ is a generalized reflexive matrix if RGS = G. The set of all m ${\times}$ n generalized reflexive matrices is denoted by $GRC^{m{\times}n}$. In this paper, an efficient method for the least squares solution $X\;{\in}\;GRC^{m{\times}n}$ of the matrix equation AXB = D with arbitrary coefficient matrices $A\;{\in}\;C^{p{\times}m}$, $B\;{\in}\;C^{n{\times}q}$and the right-hand side $D\;{\in}\;C^{p{\times}q}$ is developed based on the canonical correlation decomposition(CCD) and, an explicit formula for the general solution is presented.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.575-585
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• 2016

Longitudinal studies repeatedly measure outcomes over time. Therefore, repeated measurements are serially correlated from same subject (within-subject variation) and there is also variation between subjects (between-subject variation). The serial correlation and the between-subject variation must be taken into account to make proper inference on covariate effects (Diggle et al., 2002). However, estimation of the covariance matrix is challenging because of many parameters and positive definiteness of the matrix. To overcome these limitations, we propose autoregressive moving average Cholesky decomposition (ARMACD) for the linear mixed models. The ARMACD allows a class of flexible, nonstationary, and heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the random effects covariance matrix. We analyze a real dataset to illustrate our proposed methods.

• Journal of applied mathematics & informatics
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• v.27 no.3_4
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• pp.673-683
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• 2009

We point out: to make Hermtian matrices A and B satisfy Styan matrix inequality, the condition "positive definite property" demanded in the present literatures is not necessary. Furthermore, on the premise of abandoning positive definite property, we derive Styan matrix inequality of Hadamard product for inverse Hermitian matrices and the sufficient and necessary conditions that the equation holds in our paper.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.490-496
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• 2020

We present a method to improve the performance of the multi-channel Wiener filter in noisy environment. To build subspace-based multi-channel Wiener filter, in the case of single target source, the target speech component can be effectively estimated in the principal subspace of speech correlation matrix. The speech correlation matrix can be estimated by subtracting noise correlation matrix from signal correlation matrix based on the assumption that the cross-correlation between speech and interfering noise is negligible compared with speech correlation. However, this assumption is not valid in the presence of strong interfering noise and significant error can be induced in the principal subspace accordingly. In this paper, we propose to adjust the principal subspace vector using speech presence probability and the steering vector for the desired speech source. The multi-channel speech presence probability is derived in the principal subspace and applied to adjust the principal subspace vector. Simulation results show that the proposed method improves the performance of multi-channel Wiener filter in noisy environment.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.803-809
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• 2011

Properties of multivariate Shewhart and CUSUM charts for monitoring variance-covariance matrix, specially focused on correlation coefficient components, are investigated. The performances of the proposed charts based on control statistic Lawley-Hotelling $V_i$ and likelihood ratio test (LRT) statistic $TV_i$ are evaluated in terms of average run length (ARL). For monitoring correlation coe cient components of dispersion matrix, we found that CUSUM chart based on $TV_i$ gives relatively better performances and is more preferable, and the charts based on $V_i$ perform badly and are not recommended.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.5
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• pp.1106-1114
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• 1993

A composite material is composed of a reinforcement and a matrix, which determine mechanical characteristics of the molded part. There is no doubt that the properties of a composite material depend not only on the characteristics of the matrix but also on the structure of glass fiber mat and a fiber type of reinforcement. Therefore it is very important to study the composites of reinforcement and the matrix, and to control the fiber type in the process of molding of composite materials. In this study, the specimen was made of a glass fiber mat of 6-7mm thickness by scattering it in the air after cutting the glass fiber mat with needle punching makes change according to the type of needle and the number of times of stretching. First the sheet was made by means of a hot-press after accumulating a matrix and a glass fiber according to each mat structure of glass fiber. It was heated the manufactured sheet with the dry oven and molded it a secondary high temperature compression by a 30 ton oilhydraulic press. A definition of a correlation coefficient is showed up during this period and find it out with the relation of the fiber-matrix separation and the fiber orientation. We studied effects of the glass fiber mat structures on the correlation coefficient.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.253-259
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• 2002

The rigid body characteristics (value of mass, Position of center of mass, moments and products of inertia) of mechanical systems can be identified from FRF data or vibration spectra of rigid body motion. Therefore the accuracy of rigid body characteristics is connected directly with the accuracy of measured data for rigid body motions. In this paper, a method of improving accuracy of measurement of rigid body motion is presented. Applying rigid body theory, ail translational and rotational displacements at a tentative point on the rigid body are calculated using the measured translational displacements for several points and transfer matrix. Then the estimated displacements for the identical points are calculated using the 6 displacements of the tentative Point and transfer matrix. By using correlation coefficient between measured and estimated displacements, we can detect the existence of errors that are contained in a certain measured displacement. Consequently, the improved rigid body motion with respect to a tentative point can be obtained by eliminating the contaminated data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1689-1698
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• 1998

In this paper, we present a new method for estimating the parameters of transient-type signal in additive white Gaussian noise. This method makes use of the truncated singular value decomposition of an extended-order auto-correlation-like matrix based on the linear-prediction model. The method is tested on data consisting of two exponentially dampled sinusoidal signals with the same damping factor and different damping factor. Simulation results are illustrated to demonstrate the better performance of the method applied to the auto-correlation-like matrix than that applied to the data matrix.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.329-336
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• 2006

In this paper, we propose a method of significant term extraction within a document. The technique used is Principal Component Analysis(PCA) which is one of the multivariate analysis methods. PCA can sufficiently use term-term relationships within a document by term-term correlations. We use a correlation matrix instead of a covariance matrix between terms for performing PCA. We also try to find out thresholds of both the number of components to be selected and correlation coefficients between selected components and terms. The experimental results on 283 Korean newspaper articles show that the condition of the first six components with correlation coefficients of |0.4| is the best for extracting sentence based on the significant selected terms.

• Journal of Nutrition and Health
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• v.46 no.1
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• pp.26-33
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• 2013

The purpose of this study was to investigate the sodium intake of office workers using 24-hour urine analysis and to analyze the correlation matrix between variables. The sodium intake of the subjects (n = 137), based on a 24-hr sodium excretion period, was male (n = 56) 6072.4 mg and female (n = 81) 5,168.2 mg. Urinary sodium excretion showed significant positive correlation with BMI, frequency of eating out, expenditure of eating out, salty taste assessment and high-salt dietary behavior. Analysis of urinary sodium excretion showed significant positive correlation with intake frequencies of cabbage kimchi, broiled fish, feast noodle and rice with leaf wraps. Based on the results of multiple regression, urinary sodium excretion was found to be related to intake frequencies of cabbage kimchi, broiled fish, rice with leaf wraps and high score of high-salt dietary behavior.