• Journal of Korea Game Society
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• v.11 no.2
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• pp.39-44
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• 2011

Computer games need game formulas which express game rules by mathematical functions because the game rules are automatically processed by computers. The game formulas are usually multi-variable functions. So the design of a game formula is a complex and difficult problem because it is the same problem of the design of a multi-variable function which should satisfy the related game rules. In this paper we propose a new method which can systematically design game formulas. The purposed method is the decomposing of tree structure for a game formula by analyzing the tree structure of the operands which have single-variable functions on the lowest levels. So the design method can change the complex and difficult problem of the design of a multi-variable function to the simple and easy problem of the design of the single-variable function which should satisfy the related game rules.

• Journal for History of Mathematics
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• v.21 no.2
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• pp.81-90
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• 2008

It has been noticed the greater importance of mathematical education, particularly of multi-variable calculus in the undergraduate level with remarkable progress of all sorts of sciences requiring mathematical analysis. However, there was lack of variety of introducing the definition of differentiation of multi-variable functions - in fact, all of them basically rely on the chain rules. Here we will introduce a way of defining the geometrical differentiation of the multi-variable functions based upon our teaching experience. One of its merits is that it provides the geometric explanation of the differentiation of the multi-variable functions, so that it conveys the meaning of the differentiation better compared with the known methods.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.579-590
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• 2017

The multivariate empirical distribution function could be defined when its distribution function can be estimated. It is known that bivariate empirical distribution functions could be visualized by using Step plot and Quantile plot. In this paper, the multivariate empirical distribution plot is proposed to represent the multivariate empirical distribution function on the unit square. Based on many kinds of empirical distribution plots corresponding to various multivariate normal distributions and other specific distributions, it is found that the empirical distribution plot also depends sensitively on its distribution function and correlation coefficients. Hence, we could suggest five goodness-of-fit test statistics. These critical values are obtained by Monte Carlo simulation. We explore that these critical values are not much different from those in text books. Therefore, we may conclude that the proposed test statistics in this work would be used with known critical values with ease.

• Communications of the Korean Mathematical Society
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• v.14 no.2
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• pp.233-286
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• 1999

Berkeley의 H. Wu 교수에 의하여 1993년에 제창된 Wu 거리는 다변수 복소함수론의 기하학적 연구에 중심적인 역할을 하는 여러 불변거리 중 가장 최근에 발견되었다. 짧은 역사에도 불구하고 이 개념의 유용성이 두드러지는 점을 감안하여, 이 연구의 내용과 전망 그리고 여러 관련 문제 등을 소개하려는 것이 이 논문의 목표이다.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.87-98
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• 2017

The multivaiate empirical distribution function (MEDF) is defined in this work. The MEDF's expectation and variance are derived and we have shown the MEDF converges to its real distribution function. Based on random samples from bivariate standard normal distribution with various correlation coefficients, we also obtain MEDFs and propose two kinds of graphical methods to visualize MEDFs on two dimensional plane. One is represented with at most n stairs with similar arguments as the step function, and the other is described with at most n curves which look like bivariate quantile vector. Even though these two descriptive methods could be expressed with three dimensional space, two dimensional representation is obtained with ease and it is enough to explain characteristics of bivariate distribution functions. Hence, it is possible to visualize trivariate empirical distribution functions with three dimensional quantile vectors. With bivariate and four variate illustrative examples, the proposed MEDFs descriptive plots are obtained and explored.

• Journal of Korea Water Resources Association
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• v.30 no.6
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• pp.641-648
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• 1997

Mutual information is useful for analyzing nonlinear dependence in time series in much the same way as correlation is used to characterize linear dependence. We use multivariate kernel density estimators for the estimation of mutual information at different time lags for single and multiple time series. This approach is tested on a variety of hydrologic data sets, and suggested an appropriate delay time $ au$ at which the mutual information is almost zerothen multi-dimensional phase portraits could be constructed from measurements of a single scalar time series.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.55-63
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• 2019

In engineering problems, many random variables have correlation, and the correlation of input random variables has a great influence on reliability analysis results of the mechanical systems. However, correlated variables are often treated as independent variables or modeled by specific parametric joint distributions due to difficulty in modeling joint distributions. Especially, when there are insufficient correlated data, it becomes more difficult to correctly model the joint distribution. In this study, multivariate kernel density estimation with bounded data is proposed to estimate various types of joint distributions with highly nonlinearity. Since it combines given data with bounded data, which are generated from confidence intervals of uniform distribution parameters for given data, it is less sensitive to data quality and number of data. Thus, it yields conservative statistical modeling and reliability analysis results, and its performance is verified through statistical simulation and engineering examples.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.600-607
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• 1998

일반적인 비선형 동역학 최적화문제를 비선형 프로그래밍 문제로 변환하는데 제어변수들을 방사성 기본 함수로 근사화하는 방법이 사용되었다. 방사성 기본 함수의 계수들을 연속적으로 보정하기 위하여 최소수정기법에 기초를 둔 비선형 프로그래밍 알고리즘이 연구되었다. 이러한 알고리즘을 실제적인 다변수 제어 시스템에 적용하여 성능을 검증하였다.

• The Korean Journal of Applied Statistics
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• v.5 no.1
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• pp.103-111
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• 1992

The projection pursuit method has been gussested as a technique for the analysis of the multivariate data. This method seeks out interesting linear projections of the multivariate data onto a line of a plane to solve the curse or dimensionality. In this paper we developed the discriminant analysis by using the projection method and simulations were used for comparison between this and other existing discriminant analysis methods.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.546-549
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• 1998

다치결정도 (multiple-valued decision diagram : MDD) 와 순서화된 다치결정도 (ordered MDD:OMDD)는 다치논리함수의 표현에 폭넓게 사용된다. p치 n변수인 경우 p/sup (n-1)/으로 증가하는 노드의 수는 ROMDD(reduced OMDD)를 사용하여 현저하게 감소시킬 수 있다. 그러나 다치와 다변수의 경우에는 더욱 많은 공정을 수반하게 된다. 이러한 단점을 보완하기 위해 honghai jiang이 제안한 2치시스템에서의 input implict/output explicit 관계를 갖는 OVAG(output value array graph)를 사용하여 다치논리함수를 표현한다. 그리고 MDD 표현이 어려운 상황에서 MOVAG(multi OVAG)를 사용하여 보다 쉽게 출력값을 배열하는 그래프를 이끌어 낼 수 있다. 본 논문에서는 MOVAG의 구성방법과 회로에서 MOVAG로으 변환에 대한 알고리듬을 제안하였고, 알고리듬에 의한 결과를 MDD와 비교하여 노드수 감소에 따르는 처리속도가 개선됨을 검증하였다.