• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.152-154
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• 2007

Anew discretization method for the input-driven nonlinear continuous-time system with time delay is proposed. It is based on the combination of Taylor series expansion and first-order hold assumption. The mathematical structure of the new discretization scheme is explored. The performance of the proposed discretization procedure is evaluated by case studies. The results demonstrate that the proposed discretization scheme can assure the system requirements even though under a large sampling period. A comparison between first order hold and zero-order hold is simulated also.

• Database Research
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• v.34 no.3
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• pp.159-169
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• 2018

Discretization of continuous variables intended to improve the performance of various algorithms such as data mining by transforming quantitative variables into qualitative variables. If we use appropriate discretization techniques for data, we can expect not only better performance of classification algorithms, but also accurate and concise interpretation of results and speed improvements. Various discretization techniques have been studied up to now, and however there is still demand of research on discretization studies. In this paper, we propose a new discretization technique to set the cut-point using Wasserstein distance with considering the distribution of continuous variable values with classes of data. We show the superiority of the proposed method through the performance comparison between the proposed method and the existing proven methods.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1547-1555
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• 2017

This paper studies Bayesian test of homogeneity in contingency tables made by discretizing a continuous variable. Sometimes when we are considering events of interest in small area setup, we can think of discretization approaches about the continuous variable. If we properly discretize the continuous variable, we can find invisible relationships between areas (groups) and a continuous variable of interest. The proper discretization of the continuous variable can support the alternative hypothesis of the homogeneity test in contingency tables even if the null hypothesis was not rejected through k-sample tests involving one-way ANOVA. In other words, the proportions of variables with a particular level can vary from group to group by the discretization. If we discretize the the continuous variable, it can be treated as an analysis of the contingency table. In this case, the chi-squared test is the most commonly employed method. However, further discretization gives rise to more cells in the table. As a result, the count in the cells becomes smaller and the accuracy of the test becomes lower. To prevent this, we can consider the Bayesian approach and apply it to the setup of the homogeneity test.

• Journal of Mechanical Science and Technology
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• v.18 no.8
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• pp.1297-1305
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• 2004

In this paper, we propose a new scheme for the discretization of nonlinear systems using Taylor series expansion and the zero-order hold assumption. This scheme is applied to the sampled-data representation of a non-affine nonlinear system with constant input time-delay. The mathematical expressions of the discretization scheme are presented and the ability of the algorithm is tested for some of the examples. The proposed scheme provides a finite-dimensional representation for nonlinear systems with time-delay enabling existing controller design techniques to be applied to them. For all the case studies, various sampling rates and time-delay values are considered.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.122-132
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• 2013

In this research the development of unstructured grid discretization solution techniques is presented. The purpose is to describe such a conservative discretization scheme applied for experimental validation work. The objective of this paper is to better establish the effects of mesh generation techniques on velocity fields and particle deposition patterns to determine the optimal aerodynamic characteristics. In order to achieve the objective, the mesh surface discretization approaches used the VLA prototype manufacturing tolerance zone of the outer surface. There were 3 schemes for this discretization study implementation. They are solver validation, grid convergence study and surface tolerance study. A solver validation work was implemented for the simple 2D and 3D model to get the optimum solver for the VLA model. A grid convergence study was also conducted with a different growth factor and cell spacing, the amount of mesh can be controlled. With several amount of mesh we can get the converged amount of mesh compared to experimental data. The density around surface model can be calculated by controlling the number of element in every important and sensitive surface area of the model. The solver validation work result provided the optimum solver to employ in the VLA model analysis calculation. The convergence study approach result indicated that the aerodynamic trend characteristic was captured smooth enough compared with the experimental data. During the surface tolerance scheme, it could catch the aerodynamics data of the experiment data. The discretization studies made the validation work more efficient way to achieve the purpose of this paper.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.60-64
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• 2010

To discover association rules from nontransactional data, there have been many studies on discretization of attribute values. These studies do not reflect the change of discovered rules' confidence according to the change of the ranges of the discretized attributes, and perform the discretization stage and the rule discovery stage independently. This causes the ranges of attributes not properly discretized, thereby making the rules having high confidence excluded in the result set. To solve this problem, we propose a novel method that performs the discretization and rule discovery stages simultaneously in order to discretize ranges of attributes in such a way that the rules having high confidence are discovered well. To the end, we perform hierarchical clustering on the attributes in the right hand side of rules, then do characterization on every cluster thus obtained. The experimental result demonstrates that our method discovers the rules having high confidence better than existing methods.

• The Pure and Applied Mathematics
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• v.14 no.4
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• pp.283-287
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• 2007

An extension of the contraction mapping theorem is provided in a Banach space setting to approximate fixed points of operator equations. Our approach is justified by numerical examples where our results apply whereas the classical contraction mapping principle cannot.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2399-2410
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• 2017

In this paper, a linear matrix inequality-based sampled-data fuzzy observer design method is proposed based on the exact discretization approach. In the proposed design technique, a numerically relaxed observer design condition is obtained by using the discrete-time fuzzy Lyapunov function. Unlike the existing studies, the designed observer is robust to the uncertain premise variable because the fuzzy observer is designed under the imperfect premise matching condition, in which the membership functions of the system and observer are mismatched. In addition, we apply the proposed method to the state estimation problem of the attitude and heading reference system (AHRS). To do this, we derive a Takagi-Sugeno fuzzy model for the AHRS system, and validate the proposed method through the hardware experiment.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.307-319
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• 2013

With the rapid accumulation of microarray data, it is a significant challenge to integrate available data sets addressing the same biological questions that can provide more samples and better experimental results. Sometimes, different microarray platforms make it difficult to effectively integrate data from several studies and there is no consensus on which method is the best to produce a single and unified data set. Methods using median rank score, quantile discretization and standardization (which directly combine rescaled gene expression values) and meta-analysis (which combine the results of individual studies at the interpretative level) are reviewed. Real data examples downloaded from GEO are used to compare the performance of these methods and to evaluate if the combined data set detects more reliable information from the separated data sets or not.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.252-255
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• 2001

Modern power systems are very complex and to model them completly is impractical for electromgnetic transient studies. Therefore areas outside the immediate area of interest must be represented by some form of Frequency Dependent Network Equivalent (FDNE). In this paper a method for developing FDNE is presented and demonstrated. The FDNE is generated by Linearized Least Square fitting the frequency response of a z-domain formulation. The advantage of this approach is that a direct implementation occurs which dose not incur errors due to discretization inherent with implementing a fitting function in the s-domain. The developed FDNE is accurate and efficient.