• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.851-855
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• 2007

This paper deals with the problem of designing a linear sliding surface design for a class of uncertain systems with mismatched unstructured uncertainties. The uncertain system under consideration may have mismatched parameter uncertainties in the state matrix as well as in the input matrix. In terms of linear matrix inequalities (LMIs), we give a sufficient condition for the existence of linear sliding surfaces guaranteeing the asymptotic stability of the sliding mode dynamics. We show that our LMI condition can be less conservative than the existing conditions and our result supplement the existing results. Finally, we give a numerical example showing that our method can be better than the previous results.

• Journal of the Korean Institute of Telematics and Electronics
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• v.7 no.3
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• pp.5-11
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• 1970

Some of the coding method have been discussed by extracting characteristics from vowels and consonants of Korean characters. given letters were sampled through 3$\times$5 mesh and also constituted first matrix system which taken subpatterns of vertical Conponent as variables and then, characteristics of the letters are extracted from the second matrix system expresses by common characteristics which are combined-with first one. Single coding was obtained by scanning the characteristic pattern. a good agree between theoretical values and their measurements and the reproducing of all vowels and consonants of Korean chasacters about coding were certified on the display designed.

• Nuclear Engineering and Technology
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• v.33 no.5
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• pp.539-546
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• 2001

Systematic procedure of developing radionuclide release scenarios was established based on FEP list and Interaction Matrix for near-surface LILW repository. FEPs were screened by experts＇review in terms of domestic situation and combined into scenarios on the basis of Interaction Matrix analysis. Under the assumption of design scenario, The system domain was divided into three sections: Near-field, Far-field and Biosphere. Sub-scenarios for each section were developed, and then scenarios for entire system were built up with sub-scenarios of each section. Finally, sixteen design scenarios for near-surface repository were evaluated A reference scenario and other noteworthy scenarios were selected through experts＇scenario screening.

• ETRI Journal
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• v.37 no.6
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• pp.1251-1258
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• 2015

We investigate an image recovery method for sparse-view computed tomography (CT) using an iterative shrinkage algorithm based on a second-order approach. The two-step iterative shrinkage-thresholding (TwIST) algorithm including a total variation regularization technique is elucidated to be more robust than other first-order methods; it enables a perfect restoration of an original image even if given only a few projection views of a parallel-beam geometry. We find that the incoherency of a projection system matrix in CT geometry sufficiently satisfies the exact reconstruction principle even when the matrix itself has a large condition number. Image reconstruction from fan-beam CT can be well carried out, but the retrieval performance is very low when compared to a parallel-beam geometry. This is considered to be due to the matrix complexity of the projection geometry. We also evaluate the image retrieval performance of the TwIST algorithm -sing measured projection data.

• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.97-113
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• 2009

Collaborative filtering(CF) has been a very successful approach for building recommender system, but its widespread use has exposed to some well-known problems including sparsity and scalability problems. In order to mitigate these problems, we propose two novel models for improving the typical CF algorithm, whose names are ISCF(Item-Selected CF) and USCF(User-Selected CF). The modified models of the conventional CF method that condense the original dataset by reducing a dimension of items or users in the user-item matrix may improve the prediction accuracy as well as the efficiency of the conventional CF algorithm. As a tool to optimize the reduction of a user-item matrix, our study proposes genetic algorithms. We believe that our approach may relieve the sparsity and scalability problems. To validate the applicability of ISCF and USCF, we applied them to the MovieLens dataset. Experimental results showed that both the efficiency and the accuracy were enhanced in our proposed models.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.15-23
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• 2008

This paper considers the problem of delay-dependent guaranteed cost controller design for uncertain neutral systems with distributed delays. The system under consideration is subject to norm-bounded time-varying parametric uncertainty appearing in all the matrices of the state-space model. By constructing appropriate Lyapunov functionals and using matrix inequality techniques, a state feedback controller is designed such that the resulting closed-loop system is not only robustly stable but also guarantees an adequate level of performance for all admissible uncertainties. Furthermore, a convex optimization problem is introduced to minimize a specified cost bound. By matrix transformation techniques, the corresponding optimal guaranteed controller can be obtained by solving a linear matrix inequality. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed approach.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.1
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• pp.62-67
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• 2003

An important aspect of the study of power system markets involves the assessment of strategic behavior of participants for maximizing their profits. In models of imperfect competition of a deregulated electricity system, the key task is to find the Nash equilibrium. In this paper, the bimatrix approach for finding Nash equilibria in electricity markets is investigated. This approach determines pure and mixed equilibria using the complementarity pivot algorithim. The mixed equilibrium in the matrix approach has the equal number of non-zero property. This property makes it difficult to reproduce a smooth continuous distribution for the mixed equilibrium. This paper proposes an algorithm for adjusting the quantization value of discretization to reconstruct a continuous distribution from a discrete one.

• Journal of Power Electronics
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• v.14 no.3
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• pp.572-579
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• 2014

As a non-linear time variant system, the four-quadrant line converter of an electric multiple unit (EMU) was expressed by linear time periodic functions near an operating point and modeled by a steady-state harmonic domain matrix. The components were then combined according to the circuit connection and relations of the feedback control loops to form a complete converter model. The proposed modeling method allows the study of the amplitude of harmonic impedances to explore harmonic coupling. Moreover, the proposed method helps provide a better design for the converter controllers, as well as solves the problem in coordination operation between the EMUs and the AC supply. On-site data from an actual $CRH_2$ high-speed train were used to validate the modeling principles presented in the paper.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.163-166
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• 1993

This paper describes an parallell computing algorithm in Gauss elimination of Jacobian matrix to large-scale power system. The structure of Jacobian matrix becomes different according to ordering method of buses. In sequential computation buses are ordered to minimize the number of fill-in in the triangulation of the Jacobian matrix. The proposed method using ND(nested dissection) ordering develops the parallelism in the Gauss elimination to have balance of computing load among processes and each processor uses the sequential computation method to preserve the sparsity of matrix.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.577-590
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• 2018

Employing the covariance adjustment technique, we show that in the system of two seemingly unrelated multivariate regressions the estimator of regression coefficients can be expressed as a matrix power series, and conclude that the matrix series only has a unique simpler form. In the case that the covariance matrix of the system is unknown, we define a two-stage estimator for the regression coefficients which is shown to be unique and unbiased. Numerical simulations are also presented to illustrate its superiority over the ordinary least square estimator. Also, as an example we apply our results to the seemingly unrelated growth curve models.