• 한국정밀공학회지
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• 제15권11호
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• pp.130-136
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• 1998

This paper develops an efficient algorithm for the minimum distance calculation between two general polyhedra(convex and/or concave) in three-dimensional space. The polyhedra approximate objects using flat polygons which composed of more than three vertices. The algorithm developed in this paper basically computes minimum distance between two polygons(one polygon per object) and finds a set of two polygons which makes a global minimum distance. The advantage of the algorithm is that the global minimum distance can be computed in any cases. But the big disadvantage is that the minimum distance computing time is rapidly increased with the number of polygons which used to approximate an object. This paper develops a method to eliminate sets of two polygons which have no possibility of minimum distance occurrence, and an efficient algorithm to compute a minimum distance between two polygons in order to compensate the inherent disadvantage of the algorithm. The correctness of the algorithm is verified not only comparing analytically calculated exact minimum distance with one calculated using the developed algorithm but also watching a line which connects two points making a global minimum distance of a convex object and/or a concave object. The algorithm efficiently finds minimum distance between two convex objects made of 224 polygons respectively with a computation time of about 0.1 second.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1876-1879
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• 1997

This paper developes an efficient algorithm for the minimum distance calculation between general polyhedra(convex and/or concave). The polyhedron approximates and object using flat polygons which composed of more than three veritices. The algorithm developed in this paper basically computes minimun distance betwen two convex polygons and finds a set of polygons whcih makes a global minimum distance. The advantage of the algorithm is that the global minimum distance can be computed in any cases. But the big disadvantage is that minimum distance computing time is repidly increased with the number of polygons which used to approximate an object. This paper developes a method to eliminate unnecessary sets of polygons, and an efficinet algorithm to compute a minimum distance between two polygons in order to compensate the inherent disadvantage of the algorithm. It takes only a few times iteration to find minimum distance for msot polygons. The correctness of the algortihm are visually tested with a line which connects two points making a global minimum distance of simple convex object(box) and concave object(pipe). The algorithm can find minimum distance between two convex objects made of about 200 polygons respectively less than a second computing time.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.687-696
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• 2003

This article presents a new family of the estimating functions related with minimum distance estimations, and discusses its relationship to the family of the minimum density power divergence estimating equations. Two representative minimum distance estimations; the minimum $L_2$ distance estimation and the minimum Hellinger distance estimation are studied in the light of the theory of estimating equations. Despite of the desirable properties of minimum distance estimations, they are not widely used by general researchers, because theories related with them are complex and are hard to be computationally implemented in real problems. Hopefully, this article would be a help for understanding the minimum distance estimations better.

• Communications for Statistical Applications and Methods
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• 제16권6호
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• pp.989-995
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• 2009

Basu et al. (1998) proposed the minimum divergence estimating method which is free from using the painful kernel density estimator. Their proposed class of density power divergences is indexed by a single parameter $\alpha$ which controls the trade-off between robustness and efficiency. In this article, (1) we introduce a new large class the minimum squared distance which includes from the minimum Hellinger distance to the minimum $L_2$ distance. We also show that under certain conditions both the minimum density power divergence estimator(MDPDE) and the minimum squared distance estimator(MSDE) are asymptotically equivalent and (2) in finite samples the MDPDE performs better than the MSDE in general but there are some cases where the MSDE performs better than the MDPDE when estimating a location parameter or a proportion of mixed distributions.

• 대한전기학회논문지
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• 제43권5호
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• pp.848-860
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• 1994

Generally, to get the minimum distance between two arbitrary shapes that are composed of circular arcs and lines, we must calculate distances for all the possible pairs of the components from two given shapes. In this paper, we propose an efficient method for the minimum distance problem between two shapes by using their structural features after extracting the reduced component lists which are essential to calculate the minimum distance considering the relationship of shape location. Even though the reduced component lists may contain all the components of the shapes in the worst case, in the average we can reduce the required computation much by using the reduced component lists. This method may be efectively applied to calculating the minimum distance between two shapes which are generated by the CAD tool, like in the nesting system.

• Journal of the Korean Statistical Society
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• 제31권2호
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• pp.213-228
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• 2002

Asymptotic properties of minimum distance estimators for the parameter involved for a class of stochastic partial differential equations are investigated following the techniques in Kutoyants and Pilibossian (1994).

• 방송공학회논문지
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• 제27권7호
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• pp.974-984
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• 2022

In this paper, we introduce the minimum and maximum distance setting methods used in geometric distance attenuation processing, which is one of spatial sound reproduction methods. In general, sound attenuation by distance is inversely proportional to distance, that is 1/r law, but when the relative distance between the user and the audio object is very short or long, exceptional processing might be performed by setting the minimum distance or the maximum distance. While MPEG-I Immersive Audio's RM0 uses fixed values for the minimum and maximum distances, this study proposes effective methods for setting the distances considering the signal gain of an audio object. Proposed methods were verified through simulation of the proposed methods and experiments using RM0 renderer.

• Journal of applied mathematics & informatics
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• 제28권1_2호
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• pp.283-293
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• 2010

In this paper, inverse constrained minimum spanning tree problem under Hamming distance. Such an inverse problem is to modify the weights with bound constrains so that a given feasible solution becomes an optimal solution, and the deviation of the weights, measured by the weighted Hamming distance, is minimum. We present a strongly polynomial time algorithm to solve the inverse constrained minimum spanning tree problem under Hamming distance.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.213-220
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• 2006

Since Beran (1977) developed the minimum Hellinger distance estimation, this method has been a popular topic in the field of robust estimation. In the process of defining a distance, a kernel density estimator has been widely used as a density estimator. In this article, however, we show that a combination of a kernel density estimator and an empirical density could result a smaller bias of the minimum Hellinger distance estimator than using just a kernel density estimator for a location parameter.

• 한국통신학회논문지
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• 제25권10A호
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• pp.1576-1581
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• 2000

부호길이가 $2^{n}-1$이고 생성다항식이 g(x)=$m_1(x)m_{d}(x)$인 이진 순회부호에서 최소거리가 5가 되기 위한 조건은 $x^{d}$가 APN 함수라는 것으로 이는 이미 알려진 내용인데 이에 관한 새로운 증명을 제시하였다.