• Title/Summary/Keyword: matching theorem

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FIXED POINTS AND ALTERNATIVE PRINCIPLES

  • Park, Se-Hie;Kim, Hoon-Joo
    • Honam Mathematical Journal
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    • v.34 no.3
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    • pp.439-449
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    • 2012
  • In a recent paper, M. Balaj [B] established an alternative principle. The principle was applied to a matching theorem of Ky Fan type, an analytic alternative, a minimax inequality, and existence of solutions of a vector equilibrium theorem. Based on the first author's fixed point theorems, in the present paper, we obtain generalizations of the main result of Balaj [B] and their applications.

MATCHING THEOREMS AND SIMULTANEOUS RELATION PROBLEMS

  • Balaj, Mircea;Coroianu, Lucian
    • Bulletin of the Korean Mathematical Society
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    • v.48 no.5
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    • pp.939-949
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    • 2011
  • In this paper we give two matching theorems of Ky Fan type concerning open or closed coverings of nonempty convex sets in a topological vector space. One of them will permit us to put in evidence, when X and Y are convex sets in topological vector spaces, a new subclass of KKM(X, Y) different by any admissible class $\mathfrak{u}_c$(X, Y). For this class of set-valued mappings we establish a KKM-type theorem which will be then used for obtaining existence theorems for the solutions of two types of simultaneous relation problems.

Improvment of Accuracy of Projective Transformation Matrix for Image Mosaicing (영상 모자이킹을 위한 사영 변환 행렬의 정밀도 개선)

  • 노현영;이상욱
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.226-230
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    • 2002
  • This paper proposes a method of improvement of accuracy of projective transformation matrix for Image Mosaicing. Using shift theorem, we extracted global translation components between images and using translation components, we found matching points between images so we solve general matching point problem we extracted highly trusted matching point using RANSAC algorithm. we normalized matching point coordinates and improved accuracy of projective transformation matrix.

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ELEMENTS OF THE KKM THEORY FOR GENERALIZED CONVEX SPACE

  • Park, Se-Hei
    • Journal of applied mathematics & informatics
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    • v.7 no.1
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    • pp.1-28
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    • 2000
  • In the present paper, we introduce fundamental results in the KKM theory for G-convex spaces which are equivalent to the Brouwer theorem, the Sperner lemma, and the KKM theorem. Those results are all abstract versions of known corresponding ones for convex subsets of topological vector spaces. Some earlier applications of those results are indicated. Finally, We give a new proof of the Himmelberg fixed point theorem and G-convex space versions of the von Neumann type minimax theorem and the Nash equilibrium theorem as typical examples of applications of our theory.

Range Subsequence Matching under Dynamic Time Warping (DTW 거리를 지원하는 범위 서브시퀀스 매칭)

  • Han, Wook-Shin;Lee, Jin-Soo;Moon, Yang-Sae
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.6
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    • pp.559-566
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    • 2008
  • In this paper, we propose a range subsequence matching under dynamic time warping (DTW) distance. We exploit Dual Match, which divides data sequences into disjoint windows and the query sequence into sliding windows. However, Dual Match is known to work under Euclidean distance. We argue that Euclidean distance is a fragile distance, and thus, DTW should be supported by Dual Match. For this purpose, we derive a new important theorem showing the correctness of our approach and provide a detailed algorithm using the theorem. Extensive experimental results show that our range subsequence matching performs much better than the sequential scan algorithm.

Linear Detrending Subsequence Matching in Time-Series Databases (시계열 데이터베이스에서 선형 추세 제거 서브시퀀스 매칭)

  • Gil, Myeong-Seon;Kim, Bum-Soo;Moon, Yang-Sae;Kim, Jin-Ho
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.5
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    • pp.586-590
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    • 2010
  • In this paper we formally define the linear detrending subsequence matching and propose its efficient index-based solution. To this end, we first present the notion of LD-windows. We eliminate the linear trend from a subsequence rather than each window itself and obtain LD-windows by dividing the subsequence into windows. Using the LD-windows we present a lower bounding theorem of the index-based solution and formally prove its correctness. Based on this lower bounding theorem, we then propose the index building and subsequence matching algorithms, respectively. Finally, we show the superiority of our index- based solution through experiments.

REMARKS ON THE KKM PROPERTY FOR OPEN-VALUED MULTIMAPS ON GENERALIZED CONVEX SPACES

  • KIM HOONJOO;PARK SEHIE
    • Journal of the Korean Mathematical Society
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    • v.42 no.1
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    • pp.101-110
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    • 2005
  • Let (X, D; ${\Gamma}$) be a G-convex space and Y a Hausdorff space. Then $U^K_C$(X, Y) ${\subset}$ KD(X, Y), where $U^K_C$ is an admissible class (dup to Park) and KD denotes the class of multimaps having the KKM property for open-valued multimaps. This new result is used to obtain a KKM type theorem, matching theorems, a fixed point theorem, and a coincidence theorem.

A Numerical Study of Nonlinear Free-surface Flows Generated by Motions of Two Dimensional Cylinders (2차원 실린더의 운동에 기인한 비선형 자유표면 유동의 수치해석)

  • Lee, Ho-Young
    • Journal of Ocean Engineering and Technology
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    • v.12 no.1
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    • pp.85-98
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    • 1998
  • 본 논문의 수치해법은 경계치문제를 풀기 위하여 코시이론(Cauchy's theorem)을 사용하였다. 경계치문제는 완전한 물체표면조건과 자유표면조건을 만족시키는 초기치문제로 귀결된다. 현 수치해법에서 무한영역은 수치계산 영역인 비선형 영역과 선형 자유표면조건을 만족하는 선형영역으로 나누어진다. 선형영역의 해는 과도 그린(Green)함수를 사용하여 정합조건을 부과함으로써, 수치계산은 비선형 영역에서만 수행된다. 본 논문에서 저자는 수치계산 영역에서 코시이론을 사용하여 적분방정식을 도출하였고, 무한영역의 해는 정합면에서 과도 그린함수를 사용하여 표현하였다. 본 수치계산에서 자유표면에 요소 재분배법을 적용함으로써 쇄파현상에 대해서도 안정적인 수치해석을 할 수 있었다. 본 논문에서 개발된 수치방법을 적용한 문제는 다음과 같다. 첫째는 자유표면에서 실린더가 강제동요하는 경우에 자유표면형상과 힘을 계산하여 이전의 실험치 및 계산치와 비교하였다. 두번째로는 실린더가 자유수면하에서 일정한 속도로 항주하는 경우에는 조파저항과 양력을 계산하여 고차 스펙트럴법과 비교하였다.

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APPLICATIONS OF GRAPH THEORY

  • Pirzada, S.;Dharwadker, Ashay
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.11 no.4
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    • pp.19-38
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    • 2007
  • Graph theory is becoming increasingly significant as it is applied of mathematics, science and technology. It is being actively used in fields as varied as biochemistry(genomics), electrical engineering(communication networks and coding theory), computer science(algorithms and computation) and operations research(scheduling). The powerful results in other areas of pure mathematics. Rhis paper, besides giving a general outlook of these facts, includes new graph theoretical proofs of Fermat's Little Theorem and the Nielson-Schreier Theorem. New applications to DNA sequencing (the SNP assembly problem) and computer network security (worm propagation) using minimum vertex covers in graphs are discussed. We also show how to apply edge coloring and matching in graphs for scheduling (the timetabling problem) and vertex coloring in graphs for map coloring and the assignment of frequencies in GSM mobile phone networks. Finally, we revisit the classical problem of finding re-entrant knight's tours on a chessboard using Hamiltonian circuits in graphs.

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On the edge independence number of a random (N,N)-tree

  • J. H. Cho;Woo, Moo-Ha
    • Bulletin of the Korean Mathematical Society
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    • v.33 no.1
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    • pp.119-126
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    • 1996
  • In this paper we study the asymptotic behavior of the edge independence number of a random (n,n)-tree. The tools we use include the matrix-tree theorem, the probabilistic method and Hall's theorem. We begin with some definitions. An (n,n)_tree T is a connected, acyclic, bipartite graph with n light and n dark vertices (see [Pa92]). A subset M of edges of a graph is called independent(or matching) if no two edges of M are adfacent. A subset S of vertices of a graph is called independent if no two vertices of S are adjacent. The edge independence number of a graph T is the number $\beta_1(T)$ of edges in any largest independent subset of edges of T. Let $\Gamma(n,n)$ denote the set of all (n,n)-tree with n light vertices labeled 1, $\ldots$, n and n dark vertices labeled 1, $\ldots$, n. We give $\Gamma(n,n)$ the uniform probability distribution. Our aim in this paper is to find bounds on $\beta_1$(T) for a random (n,n)-tree T is $\Gamma(n,n)$.

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