• Title/Summary/Keyword: Higher order convergence

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MULTIGRID METHOD FOR AN ACCURATE SEMI-ANALYTIC FINITE DIFFERENCE SCHEME

  • Lee, Jun-S.
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.7 no.2
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    • pp.75-81
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    • 2003
  • Compact schemes are shown to be effective for a class of problems including convection-diffusion equations when combined with multigrid algorithms [7, 8] and V-cycle convergence is proved[5]. We apply the multigrid algorithm for an semianalytic finite difference scheme, which is desinged to preserve high order accuracy despite of singularities.

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Optimum design of Steelbox Girder Bridges using Improved Higher-order Convex Approximation (고차 Convex 근사화기법을 이용한 강상자형교의 최적설계)

  • 조효남;민대홍;이광민;김성헌
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2003.04a
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    • pp.201-208
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    • 2003
  • Since the real steel box girder bridges have a large number of design variables and show complex structural behavior, it would be impractical to directly use the algorithm for its optimum design. Thus, in this study, for optimum design of real steel box girder bridge, approximated reanalysis using an higher-order Improved self-adjusted Convex Approximation (ISACA) which was newly proposed on a previous study by the author is applied for the numerical efficiency. To demonstrate the efficiency, robustness, and convergence of the approximated reanalysis technique using the ISACA, a real bridge having two continuous spans is used as an illustrative example. From the results of the numerical investigation, it may be positively stated that the efficiency, robustness, and convergence of the approximated reanalysis using an ISACA is superior compared with the previous approximated reanalysis techniques.

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A CRANK-NICOLSON CHARACTERISTIC FINITE ELEMENT METHOD FOR SOBOLEV EQUATIONS

  • Ohm, Mi Ray;Shin, Jun Yong
    • East Asian mathematical journal
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    • v.32 no.5
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    • pp.729-744
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    • 2016
  • A Crank-Nicolson characteristic finite element method is introduced to construct approximate solutions of a Sobolev equation with a convection term. The higher order of convergences in the temporal direction and in the spatial direction in $L^2$ normed space are verified for the Crank-Nicolson characteristic finite element method.

Contribution analysis of carcass traits on auction price for Hanwoo in Gyeonggi province

  • Yun, Jewoong;Kim, Yoseph;Lee, Jieun;Kang, Tae Hun;Kim, Myunghoo;Seo, Jakyeom;Cho, Seong-Keun;Kim, Byeong-Woo
    • Korean Journal of Agricultural Science
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    • v.48 no.3
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    • pp.367-375
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    • 2021
  • The aim of this study was to identify the factors contributing to the auction price and total price of carcasses by using squared semi-partial correlation of carcass traits. The data used in this study were the carcass grades assigned to 7,145 head of Hanwoo slaughtered from 2013 to 2018 in Gyeonggi province and 106,779 head of Hanwoo slaughtered from 2013 to 2018 outside of Gyeonggi province. The rankings of the carcass traits contributing to the auction price were in the order of marbling score (86.70%), backfat thickness (10.42%), eye muscle area (1.40%), and carcass weight (0.92%) in Gyeonggi province. In Hanwoo slaughtered outside of Gyeonggi province, the rankings were in the order of marbling score (88.53%), backfat thickness (9.06%), eye muscle area (1.24%), and carcass weight (0.99%). The rankings of carcass traits contributing to the total price were in the order of marbling score (45.95%), carcass weight (45.60%), backfat thickness (6.49%) and eye muscle area (0.77%) in Gyeonggi province. In Hanwoo slaughtered outside Gyeonggi province, the rankings were in the order of marbling score (49.64%), carcass weight (43%), backfat thickness (5.86%), and eye muscle area (0.66%). Gyeonggi province Hanwoo had thinner backfat thickness than Hanwoo outside Gyeonggi, and it had a higher contribution to auction price and total price. Collectively, Hanwoo in Gyeonggi province showed higher contribution scores for backfat thickness. This study aimed to provide basic information to guide Hanwoo breeding and increase profits for Hanwoo farms through the analysis of each traits according to environmental factors.

An Exploratory Study on Convergence generation according to the convergence level estimation of Digital Device and Service (디지털기기와 디지털서비스의 컨버전스 수준 평가에 따른 컨버전스 세대의 탐색적 고찰)

  • Kim, Yeon-Jeong
    • Journal of Digital Convergence
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    • v.9 no.4
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    • pp.169-179
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    • 2011
  • The purpose of this study are as follows. First, to analyze digital convergence level of convergence generation to demographic variables. Second, the convergence level to digital device and using frequency to digital service. Third, the convergence level to digital service and using frequency to digital service. The research methods FGI, the interview with IT expert group and survey. The results of research are as follows. First, 30 aging, expert group, higher education group over graduate school are actively using and participated. Second, high level of convergence device are smart-phone, tablet PC, net-book are in order. high level of convergence service are SNS service, twitter, uee, portal messenger and app store, e-Book, web hard are in order. Third, The convergence generation enjoying app-store of smartphone, wireless game and more participating facebook/cyworld twitter, Portal, internet community.

Parallel M-band DWT-LMS Algorithm to Improve Convergence Speed of Nonlinear Volterra Equalizer in MQAM System with Nonlinear HPA (비선형 HPA를 가진 M-QAM 시스템에서 비선형 Volterra 등화기의 수렴 속도 향상을 위한 병렬 M-band DWT-LMS 알고리즘)

  • Choi, Yun-Seok;Park, Hyung-Kun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.7C
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    • pp.627-634
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    • 2007
  • When a higher-order modulation scheme (16QAM or 64QAM) is applied to the communications system using the nonlinear high power amplifier (HPA), the performance can be degraded by the nonlinear distortion of the HPA. The nonlinear distortion can be compensated by the adaptive nonlinear Volterra equalizer using the low-complexity LMS algorithm at the receiver. However, the LMS algorithm shows very slow convergence performance. So, in this paper, the parallel M-band discrete wavelet transformed LMS algorithm is proposed in order to improve the convergence speed. Throughout the computer simulations, it is shown that the convergence performance of the proposed method is superior to that of the conventional time-domain and transform-domain LMS algorithms.

ITERATIVE REWEIGHTED ALGORITHM FOR NON-CONVEX POISSONIAN IMAGE RESTORATION MODEL

  • Jeong, Taeuk;Jung, Yoon Mo;Yun, Sangwoon
    • Journal of the Korean Mathematical Society
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    • v.55 no.3
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    • pp.719-734
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    • 2018
  • An image restoration problem with Poisson noise arises in many applications of medical imaging, astronomy, and microscopy. To overcome ill-posedness, Total Variation (TV) model is commonly used owing to edge preserving property. Since staircase artifacts are observed in restored smooth regions, higher-order TV regularization is introduced. However, sharpness of edges in the image is also attenuated. To compromise benefits of TV and higher-order TV, the weighted sum of the non-convex TV and non-convex higher order TV is used as a regularizer in the proposed variational model. The proposed model is non-convex and non-smooth, and so it is very challenging to solve the model. We propose an iterative reweighted algorithm with the proximal linearized alternating direction method of multipliers to solve the proposed model and study convergence properties of the algorithm.

Blind Image Separation with Neural Learning Based on Information Theory and Higher-order Statistics (신경회로망 ICA를 이용한 혼합영상신호의 분리)

  • Cho, Hyun-Cheol;Lee, Kwon-Soon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.8
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    • pp.1454-1463
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    • 2008
  • Blind source separation by independent component analysis (ICA) has applied in signal processing, telecommunication, and image processing to recover unknown original source signals from mutually independent observation signals. Neural networks are learned to estimate the original signals by unsupervised learning algorithm. Because the outputs of the neural networks which yield original source signals are mutually independent, then mutual information is zero. This is equivalent to minimizing the Kullback-Leibler convergence between probability density function and the corresponding factorial distribution of the output in neural networks. In this paper, we present a learning algorithm using information theory and higher order statistics to solve problem of blind source separation. For computer simulation two deterministic signals and a Gaussian noise are used as original source signals. We also test the proposed algorithm by applying it to several discrete images.

Dynamic Reanalysis of Base-Isolated Systems Using a Perturbation Technique (섭동법에 의한 면진구조계의 동적 재해석)

  • Kim, Hee-duck
    • Journal of the Korean Society of Industry Convergence
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    • v.4 no.2
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    • pp.167-175
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    • 2001
  • In this study, a general perturbation method is presented to reanalysis dynamic response of base-isolated systems. The perturbation is expanded to general order and which provide the formulation of perturbed solutions. in which eigensolutions of non-modified system are treated as unperturbed solutions. The accuracy of present method is tested using a 2-DOF system with isolator, where the stiffness and damping coefficients of isolator are changed, respectively, The reanalyzed eigensolutions and response using perturbed solutions are successfully approached to exact ones after just first perturbation. Supposing the practical criterion as ${\pm}5%$ error, the modification range of -50%~30% from original system can be allowed for the first order perturbation. Using higher order solutions, the applicable range will be wide.

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A GLOBALLY AND SUPERLIEARLY CONVERGENT FEASIBLE SQP ALGORITHM FOR DEGENERATE CONSTRAINED OPTIMIZATION

  • Chen, Yu;Xie, Xiao-Liang
    • Journal of applied mathematics & informatics
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    • v.28 no.3_4
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    • pp.823-835
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    • 2010
  • In this paper, A FSQP algorithm for degenerate inequality constraints optimization problems is proposed. At each iteration of the proposed algorithm, a feasible direction of descent is obtained by solving a quadratic programming subproblem. To overcome the Maratos effect, a higher-order correction direction is obtained by solving another quadratic programming subproblem. The algorithm is proved to be globally convergent and superlinearly convergent under some mild conditions. Finally, some preliminary numerical results are reported.