• 제목/요약/키워드: Point kernel

검색결과 196건 처리시간 0.028초

Convergence Analysis on Bilateral Filter with a Fixed Point Iteration (고정점 반복을 이용한 양방향 필터의 수렴 분석)

  • Ham, Bumsub;Sohn, Kwanghoon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 한국방송공학회 2011년도 하계학술대회
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    • pp.11-13
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    • 2011
  • 양방향 필터 (Bilateral filter)는 에지 보전 평활화 필터로써 디노이징, 반사 제거, 스테레오 매칭 등 다양한 분야에서 사용되고 있다. 이는 기존의 가우시안 필터에 사용되는 공간 도메인 커널 (spatial kernel)이외에 강도 도메인 커널 (range kernel)을 추가로 사용하여 비슷한 강도의 픽셀에 높은 가중치를 부여함으로써 에지를 보전하면서 평활화를 한다. 또한 양방향 필터는 비등방성 확산 필터 (Anisotropic diffusion filter)와 달리 항상 수렴을 보장한다. 따라서 본 논문에서는 고정점 반복 이론을 적용하여 양방향 필터의 수렴을 수학적으로 증명한다.

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Local linear regression analysis for interval-valued data

  • Jang, Jungteak;Kang, Kee-Hoon
    • Communications for Statistical Applications and Methods
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    • 제27권3호
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    • pp.365-376
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    • 2020
  • Interval-valued data, a type of symbolic data, is given as an interval in which the observation object is not a single value. It can also occur frequently in the process of aggregating large databases into a form that is easy to manage. Various regression methods for interval-valued data have been proposed relatively recently. In this paper, we introduce a nonparametric regression model using the kernel function and a nonlinear regression model for the interval-valued data. We also propose applying the local linear regression model, one of the nonparametric methods, to the interval-valued data. Simulations based on several distributions of the center point and the range are conducted using each of the methods presented in this paper. Various conditions confirm that the performance of the proposed local linear estimator is better than the others.

Smoothing Parameter Selection in Nonparametric Spectral Density Estimation

  • Kang, Kee-Hoon;Park, Byeong-U;Cho, Sin-Sup;Kim, Woo-Chul
    • Communications for Statistical Applications and Methods
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    • 제2권2호
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    • pp.231-242
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    • 1995
  • In this paper we consider kernel type estimator of the spectral density at a point in the analysis of stationary time series data. The kernel entails choice of smoothing parameter called bandwidth. A data-based bandwidth choice is proposed, and it is obtained by solving an equation similar to Sheather(1986) which relates to the probability density estimation. A Monte Carlo study is done. It reveals that the spectral density estimates using the data-based bandwidths show comparatively good performance.

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Study on the Extraction of Nuclear Power Plant Failure Patterns using AAKR (AAKR을 이용한 원자력 발전소 고장 패턴 추출에 관한 연구)

  • Park, Kibeom;Ahn, Hongmin;Kang, Seongki;Chai, Jangbom
    • Transactions of the Korean Society of Pressure Vessels and Piping
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    • 제13권1호
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    • pp.40-47
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    • 2017
  • In this paper, we investigate the feasibility of a strategy of failure detection and identification. The point of proposed strategy includes a pattern extraction approach for failure identification using Auto-Associative Kernel Regression (AAKR). We consider a simulation data concerning 605 signals of a Generic Pressurized Water Reactor(GPWR). In the application, the reconstructions are provided by a set of AAKR models, whose input signals have been selected by Correlation Analysis(CA) for the identification of the groups. The failure pattern is extracted by analyzing the residuals of observations and reconstructions. We present the possibility of extraction of patterns for six failure.

A Case Study of an Activity Based Mathematical Education: A Kernel Density Estimation to Solve a Dilemma for a Missile Simulation

  • Kim, G. Daniel
    • Communications of Mathematical Education
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    • 제16권
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    • pp.139-147
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    • 2003
  • While the statistical concept 'order statistics' has a great number of applications in our society ranging from industry to military analysis, it is not necessarily an easy concept to understand for many people. Adding some interesting simulation activities of this concept to the probability or statistics curriculum, however, can enhance the learning curve greatly. A hands-on and a graphic calculator based activities of a missile simulation were introduced by Kim(2003) in the context of order statistics. This article revisits the two activities in his paper and point out a dilemma that occurs from the violation of an assumption on two deviation parameters associated with the missile simulation. A third activity is introduced to resolve the dilemma in the terms of a kernel density estimation which is a nonparametric approach.

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A Study on the Trade Area Analysis Model based on GIS - A Case of Huff probability model - (GIS 기반의 상권분석 모형 연구 - Huff 확률모형을 중심으로 -)

  • Son, Young-Gi;An, Sang-Hyun;Shin, Young-Chul
    • Journal of the Korean Association of Geographic Information Studies
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    • 제10권2호
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    • pp.164-171
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    • 2007
  • This research used GIS spatial analysis model and Huff probability model and achieved trade area analysis of area center. we constructed basic maps that were surveyed according to types of business, number of households etc. using a land registration map of LMIS(Land Management Information System) in Bokdae-dong, Cheongju-si. Kernel density function and NNI(Nearest Neighbor Index) was used to estimate store distribution center area in neighborhood life zones. The center point of area and scale were estimated by means of the center area. Huff probability model was used in abstracting trade areas according to estimated center areas, those was drew map. Therefore, this study describes method that can apply in Huff probability model through kernel density function and NNI of GIS spatial analysis techniques. A trade area was abstracted more exactly by taking advantage of this method, which will can aid merchant for the foundation of small sized enterprises.

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Electromagnetic Field Analysis Using the Point Collocation Method Based on the FMLSRK Approximation

  • Kim, Hong-Kyu;Chong, Jin-Kyo;Park, Kyong-Yop;Kim, Do-Wan
    • KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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    • 제4B권4호
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    • pp.180-183
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    • 2004
  • This paper presents a description of the point collocation method and its application to the electromagnetic field computation. The interpolation scheme is based on the fast moving least square reproducing kernel approximation. In the method, the integration cell is not required and the essential boundary conditions can be enforced directly. Numerical simulations on 1-D and 2-D problems are carried out to validate the method. It is found that computational efficiency is higher than the general mesh-free methods.

WEAKLY EINSTEIN CRITICAL POINT EQUATION

  • Hwang, Seungsu;Yun, Gabjin
    • Bulletin of the Korean Mathematical Society
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    • 제53권4호
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    • pp.1087-1094
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    • 2016
  • On a compact n-dimensional manifold M, it has been conjectured that a critical point of the total scalar curvature, restricted to the space of metrics with constant scalar curvature of unit volume, is Einstein. In this paper, after derivng an interesting curvature identity, we show that the conjecture is true in dimension three and four when g is weakly Einstein. In higher dimensional case $n{\geq}5$, we also show that the conjecture is true under an additional Ricci curvature bound. Moreover, we prove that the manifold is isometric to a standard n-sphere when it is n-dimensional weakly Einstein and the kernel of the linearized scalar curvature operator is nontrivial.

A fast DCT algorithm with reduced propagation error in the fixed-point compuitation (고정 소수점 연산시 오차의 전파를 줄이는 고속 이산 여현 변환 알고리즘)

  • 정연식;이임건;최영호;박규태
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제23권9A호
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    • pp.2365-2371
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    • 1998
  • Discrete cosine transform (DCT) has wide applications in speech and image coding. In this paper, we propose a novel fast dCT scheme with the property of reduced multiplication stages and the smaller number of additions and multiplications. This exploits the symmetry property of the DCT kernel to decompose the N-point dCT to N/2 point, and can be generally applied recursively to $2^{m}$-point. The proposed algorithm has a structure that most of multiplications tend to be performed at final stage, and this reduces propagation of truncation error which could occur in the fixed-point computation. Also the minimization of the multiplication stages further decreases the error.

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The East Moving Least Square Reproducing Kernel Approximation and Point Collocation Method (고속 최소 자승법을 이용한 점별 계산법)

  • 김용식;김도완
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 한국전산구조공학회 2002년도 가을 학술발표회 논문집
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    • pp.567-574
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    • 2002
  • 새로운 자유격자 관사를 이용한 점별 계산법을 제안한다 이동 최소 자승법을 이용한 기저의 생성과 기저의 근사적 미분을 동시에 구해내는 자유격자 근사를 유도하여, 직접 점별 계산법을 고안하였다. 기존의 자유 격자 법에서는 기저의 직접 미분을 사용하므로 높은 계산 비용이 필요하지만, 이 논문에서 제안된 방법은 기저의 생성과 동시에 기저의 근사적 미분을 구하게 된다. 또한 기존의 방법에서 필요하였던, 창 함수(window function)의 미분가능성을 연속성으로 대치할 수 있으므로, 주어진 문제에 따라 다양한 창 함수를 이용할 수 있다. 기저의 재생성과 interpolation의 수렴성을 소개하고, 수치 예제로서, Poisson 문제를 통해 이 방법의 유효함을 보인다.

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