• Sleep Medicine and Psychophysiology
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• v.8 no.1
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• pp.67-71
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• 2001

Independent Component Analysis (ICA) is a blind source separation method using unsupervised learning and mutual information theory created in the late eighties and developed in the nineties. It has already succeeded in separating eye movement artifacts from human scalp EEG recording. Several characteristic sleep waves such as sleep spindle, K-complex, and positive occipital sharp transient of sleep (POSTS) can be recorded during sleep EEG recording. They are used as stage determining factors of sleep staging and might be reflections of unknown neural sources during sleep. We applied the ICA method to sleep EEG for sleep waves separation. Eighteen channel scalp longitudinal bipolar montage was used for the EEG recording. With the sampling rate of 256Hz, digital EEG data were converted into 18 by n matrix which was used as a original data matrix X. Independent source matrix U (18 by n) was obtained by independent component analysis method ($U=W{\timex}X$, where W is an 18 by 18 matrix obtained by ICA procedures). ICA was applied to the original EEG containing sleep spindle, K-complex, and POSTS. Among the 18 independent components, those containing characteristic shape of sleep waves could be identified. Each independent component was reconstructed into original montage by the product of inverse matrix of W (inv(W)) and U. The reconstructed EEG might be a separation of sleep waves without other components of original EEG matrix X. This result (might) demonstrates that characteristic sleep waves may be separated from original EEG of unknown mixed neural origins by the Independent Component Analysis (ICA) method.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.43-50
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• 2017

According to living environment, the number of deaths due to thyroid diseases increased. In this paper, we proposed an algorithm for recognizing a thyroid detection using texture analysis based on shape, gray level co-occurrence matrix and gray level run length matrix. First of all, we segmented the region of interest (ROI) using active contour model algorithm. Then, we applied a total of 18 features (5 first order descriptors, 10 Gray level co-occurrence matrix features(GLCM), 2 Gray level run length matrix features and shape feature) to each thyroid region of interest. The extracted features are used as statistical analysis. Our results show that first order statistics (Skewness, Entropy, Energy, Smoothness), GLCM (Correlation, Contrast, Energy, Entropy, Difference variance, Difference Entropy, Homogeneity, Maximum Probability, Sum average, Sum entropy), GLRLM features and shape feature helped to distinguish thyroid benign and malignant. This algorithm will be helpful to diagnose of thyroid nodule on ultrasound images.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.485-493
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• 2004

This paper presents the interesting properties of a certain patterned matrix that plays an significant role in the statistical analysis. The necessary and sufficient condition on the existence of the inverse of the patterned matrix and its determinant are derived. In special cases of the patterned matrix, explicit formulas for its inverse, determinant and the characteristic equation are obtained.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.4
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• pp.455-459
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• 1986

A large set of linear equations which arise in many applications, such as in digital signal processing, image filtering, estimation theory, numerical analysis, etc. involve the problem of a tridiagonal matrix. In this paper, the determinant, eigenvalue and inverse matrix of a tridiagoanl matrix are analytically evaluated.

• 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.

• International Journal of Automotive Technology
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• v.2 no.3
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• pp.117-122
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• 2001

For a dynamic analysis of a constrained multibody system, it is necessary to have a routine for satisfying kinematic constraints. LU decomposition scheme, which is used to divide coordinates into dependent and independent coordinates, is efficient but has great difficulty near the singular configuration. Other method such as the projection matrix, which is more stable near a singular configuration, takes longer simulation time due to the large amount of calculation for decomposition. In this paper, the row space and the null space of the Jacobian matrix are proposed by using the pseudo-inverse method and the projection matrix. The equations of the motion of a system are replaced with independent acceleration components using the null space of the Jacobian matrix. Also a new hybrid method is proposed, combining the LU decomposition and the projection matrix. The proposed hybrid method has following advantages. (1) The simulation efficiency is preserved by the LU method during the simulation. (2) The accuracy of the solution is also achieved by the projection method near the singular configuration.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.273-290
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• 2006

This study suggests a frequency matrix technique to predict personal credit rate more efficiently using incomplete data sets. At first this study test on multiple discriminant analysis and logistic regression analysis for predicting personal credit rate with incomplete data sets. Missing values are predicted with mean imputation method and regression imputation method here. An artificial neural network and frequency matrix technique are also tested on their performance in predicting personal credit rating. A data set of 8,234 customers in 2004 on personal credit information of Bank A are collected for the test. The performance of frequency matrix technique is compared with that of other methods. The results from the experiments show that the performance of frequency matrix technique is superior to that of all other models such as MDA-mean, Logit-mean, MDA-regression, Logit-regression, and artificial neural networks.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.143-152
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• 1999

The competitive advantage of technologies is required for survival of enterprises in the social environments which change rapidly. So the strategy of technology development becomes more and more important. For the establishment of strategy, the situational analysis and the forecasting analysis are executed and they include the technology assessment and the technology forecasting. This research is intended to find out the problems and the difficulties in the current Matrix Method, and to improve the method, finally to help the R&D departments of enterprises applying the method. The suggested matrix(TSM : Technology Shift Matrix) method is designed so that one can judge the current situation of technology and future trend, by moving the matrix which is placed to the upside of the basic matrix.

• Structural Engineering and Mechanics
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• v.70 no.2
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• pp.199-207
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• 2019

In this paper, a semi-analytical method will be discussed for free vibration analysis of rotating beams with variable cross sectional area. For this purpose, the rotating beam is discretized through applying the transfer matrix method and assumed the axial force is constant for each element. Then, the transfer matrix is derived based on Euler-Bernoulli's beam differential equation and applying boundary conditions. In the following, the frequencies of the rotating beam with constant and variable cross sections are determined using the transfer matrix method in several case studies. In order to eliminate numerical difficulties in the transfer matrix method, the Riccati transfer matrix is employed for high rotation speed and high modes. The results are compared with the results of the finite elements method and Rayleigh-Ritz method which show good agreement in spite of low computational cost.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.310-316
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• 2008

This theory focuses on the Enterprise Portal and researches and analyzes the user requirement on as-is system. The UI Checklist Matrix is made based on the result of user analysis and evaluation of checklist. The horizontal axis of the Matrix is composed of 6 results(Layout, Navigation, Information, Function, Visibility and Interaction) of user requirement analysis. The vertical axis of the Matrix is composed of 10 subjects, Learnability, Efficiency, Accuracy, Accessibility, Consistency, Agility, Convergence, Personalization, Technology, and Standardization. At the point of vertical and horizontal items meet, indicates the graded of importance and defines a details item. The Guideline in which Matrix is reflected is set and according to the guideline, designing the business screen and assessing the Matrix.