• Title/Summary/Keyword: norm

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A NOTE ON FUNCTIONAL LIMIT THEOREM FOR THE INCREMENTS OF FBM IN SUP-NORM

  • Hwang, Kyo-Shin
    • East Asian mathematical journal
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    • v.24 no.3
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    • pp.275-287
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    • 2008
  • In this paper, using large deviation results for Gaussian processes, we establish some functional limit theorems for increments of a fractional Brownian motion in the usual sup-norm via estimating large deviation probabilities for increments of a fractional Brownian motion.

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Analysis on a Minimum Infinity-norm Solution for Kinematically Redundant Manipulators

  • Insoo Ha;Lee, Jihong
    • Transactions on Control, Automation and Systems Engineering
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    • v.4 no.2
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    • pp.130-139
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    • 2002
  • In this paper, at first, we investigate existing algorithms for finding the minimum infinity-norm solution of consistent linear equations and then propose a new algorithm. The proposed algorithm is intended to includes the advantages of computational efficiency as well as geometric explicitness. As a practical application example, optimum trajectory planning for redundant robot manipulators is considered. Also, an efficient approach avoiding discontinuity in trajectory is proposed by resolving the non-uniqueness problem of minimum infinity-norm solution. To be specific, the proposed method for checking possible discontinuity does not need any other algorithms in checking the possibility of discontinuity while previous work needs specially designed checking courses. To show the usefulness of the proposed techniques, an example calculating minimum infinity-norm solution for comparing the computational efficiency as well as the trajectory planning for a redundant robot manipulator are included.

A Comparative Analysis of the Relevance Weighted Boolean Model and the P-NORM Model: An Improvement on the Boolean Retrieval (적합성 가중치 검색 및 P-NORM 검색에 관한 연구 -불 논리 검색의 개선을 중심으로-)

  • 이효숙
    • Journal of the Korean Society for information Management
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    • v.11 no.1
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    • pp.31-56
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    • 1994
  • To evaluate the retrieval effectiveness of the B03lean Request Conversion Mod4 the Relevance Weighted Boolean Model, and the P-NORM Model, the present study has been done with expenmental tests. It is proven that the Relevance Weighted Bdean Model is more effective in precision and the document output ranks than the other ones. The expenmental results indmte a promisii application of relevance mformation and weigh- schemes.

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A note on T-sum of bell-shaped fuzzy intervals

  • Hong, Dug-Hun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.6
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    • pp.804-806
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    • 2007
  • The usual arithmetic operations on real numbers can be extended to arithmetical operations on fuzzy intervals by means of Zadeh's extension principle based on a t-norm T. Dombi and Gyorbiro proved that addition is closed if the Dombi t-norm is used with two bell-shaped fuzzy intervals. Recently, Hong [Fuzzy Sets and Systems 158(2007) 739-746] defined a broader class of bell-shaped fuzzy intervals. Then he study t-norms which are consistent with these particular types of fuzzy intervals as applications of a result proved by Mesiar on a strict f-norm based shape preserving additions of LR-fuzzy intervals with unbounded support. In this note, we give a direct proof of the main results of Hong.

ROBUST $L_{p}$-NORM ESTIMATORS OF MULTIVARIATE LOCATION IN MODELS WITH A BOUNDED VARIANCE

  • Georgly L. Shevlyakov;Lee, Jae-Won
    • The Pure and Applied Mathematics
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    • v.9 no.1
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    • pp.81-90
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    • 2002
  • The least informative (favorable) distributions, minimizing Fisher information for a multivariate location parameter, are derived in the parametric class of the exponential-power spherically symmetric distributions under the following characterizing restrictions; (i) a bounded variance, (ii) a bounded value of a density at the center of symmetry, and (iii) the intersection of these restrictions. In the first two cases, (i) and (ii) respectively, the least informative distributions are the Gaussian and Laplace, respectively. In the latter case (iii) the optimal solution has three branches, with relatively small variances it is the Gaussian, them with intermediate variances. The corresponding robust minimax M-estimators of location are given by the $L_2$-norm, the $L_1$-norm and the $L_{p}$ -norm methods. The properties of the proposed estimators and their adaptive versions ar studied in asymptotics and on finite samples by Monte Carlo.

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Optimal iterative learning control with model uncertainty

  • Le, Dang Khanh;Nam, Taek-Kun
    • Journal of Advanced Marine Engineering and Technology
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    • v.37 no.7
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    • pp.743-751
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    • 2013
  • In this paper, an approach to deal with model uncertainty using norm-optimal iterative learning control (ILC) is mentioned. Model uncertainty generally degrades the convergence and performance of conventional learning algorithms. To deal with model uncertainty, a worst-case norm-optimal ILC is introduced. The problem is then reformulated as a convex minimization problem, which can be solved efficiently to generate the control signal. The paper also investigates the relationship between the proposed approach and conventional norm-optimal ILC; where it is found that the suggested design method is equivalent to conventional norm-optimal ILC with trial-varying parameters. Finally, simulation results of the presented technique are given.

A Study on Factors Influencing the Performance of the Knowledge Management System(KMS): Focused on Subjective Norm and Personality (지식관리시스템의 성과에 영향을 미치는 요인에 관한 연구: 주관적 규범, 성격특성을 중심으로)

  • Kang, Mun-Sang;Kang, Sung-Bae;Shin, Mun-Bong
    • Knowledge Management Research
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    • v.12 no.5
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    • pp.71-87
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    • 2011
  • This study focuses on influencing factors of TAM on personality, subjective norm and then examines the relationship between influencing factors such as KMS usage and system performance. The survey was collected from KMS users by e-mail and on-line questionnaire. Finally, 206 questionnaires were chosen for the analysis of data. It was analyzed by SPSS and AMOS for the frequency analysis, reliability analysis, CFA(Confirmatory Factor Analysis) and SEM(Structural Equation Modeling). The results were as follows. First, subjective norm is found to be especially important to KMS usage. Second, Extraversion positively moderated the relationship between subjective norm and perceived usefulness. Third, KMS usage is significant to personal performance such as knowledge growth, decision making and the ability of problem solving. This study proposed that the usage of Knowledge Management System positively contributes to the improvement of personal performance.

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Effects of Massage on Musculoskeletal Ultrasound and Heart Rate Variability in Middle Age Women of Office Worker

  • Yon, Jung-Min;Lee, Og-Kyoung
    • Biomedical Science Letters
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    • v.19 no.1
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    • pp.55-60
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    • 2013
  • This study was to know the effects of massage on the back region in order to reduce stress in middle age women. To investigate the effects of massage to the stress levels of middle aged women, we evaluated blood pressure (BP), heart rate variability (HRV), and ultrasonography before and after back massage. The blood pressure after massage was reduced when compared to that of pre-massage. The HRV spectrum analysis was used Frequency domain analysis such as Mean HRV, normalized low frequency (norm LF), norm high frequency (norm HF), and LF/HF ratio. Post-massage BP tended to be low, but not statistical significant. After Massage, the Mean HRV, norm LF, and LF/HF ratio were significantly reduced, while norm HF was significantly increased as compared with pre-massage. The muscle layer and fat layer were significantly diminished by massage. The study was suggested that massage may be an effective treatment for relief of stress.

A PARAMETER ESTIMATION METHOD FOR MODEL ANALYSIS

  • Oh Se-Young;Kwon Sun-Joo;Yun Jae-Heon
    • Journal of applied mathematics & informatics
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    • v.22 no.1_2
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    • pp.373-385
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    • 2006
  • To solve a class of nonlinear parameter estimation problems, a method combining the regularized structured nonlinear total least norm (RSNTLN) method and parameter separation scheme is suggested. The method guarantees the convergence of parameters and has an advantages in reducing the residual norm over the use of RSNTLN only. Numerical experiments for two models appeared in signal processing show that the suggested method is more effective in obtaining solution and parameter with minimum residual norm.