• Title/Summary/Keyword: distribution parameter

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Analysis and Modeling of Clock Grid Network Using S-parameter (S-파라미터를 사용한 클락 그리드 네트워크의 분석과 모델링)

  • Kim, Kyung-Ki
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.44 no.12
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    • pp.37-42
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    • 2007
  • Clock grid networks are now common in most high performance microprocessors. This paper presents a new effective modeling and simulation methodology for the clock grid using scattering parameter. It also shows the effect of wire width and grid size on the clock skew of the grid. The interconnection of the clock grid is modeled by RC passive elements. The results show that the error is within 10 % comparing to Hspice simulation results.

Design of Adaptive Neural Networks Based Path Following Controller Under Vehicle Parameter Variations (차량 파라미터 변화에 강건한 적응형 신경회로망 기반 경로추종제어기)

  • Shin, Dong Ho
    • Journal of Drive and Control
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    • v.17 no.1
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    • pp.13-20
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    • 2020
  • Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

Extended Quasi-likelihood Estimation in Overdispersed Models

  • Kim, Choong-Rak;Lee, Kee-Won;Chung, Youn-Shik;Park, Kook-Lyeol
    • Journal of the Korean Statistical Society
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    • v.21 no.2
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    • pp.187-200
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    • 1992
  • Samples are often found to be too heterogeneous to be explained by a one-parameter family of models in the sense that the implicit mean-variance relationship in such a family is violated by the data. This phenomenon is often called over-dispersion. The most frequently used method in dealing with over-dispersion is to mix a one-parameter family creating a two parameter marginal mixture family for the data. In this paper, we investigate performance of estimators such as maximum likelihood estimator, method of moment estimator, and maximum quasi-likelihood estimator in negative binomial and beta-binomial distribution. Simulations are done for various mean parameter and dispersion parameter in both distributions, and we conclude that the moment estimators are very superior in the sense of bias and asymptotic relative efficiency.

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A convenient approach for penalty parameter selection in robust lasso regression

  • Kim, Jongyoung;Lee, Seokho
    • Communications for Statistical Applications and Methods
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    • v.24 no.6
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    • pp.651-662
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    • 2017
  • We propose an alternative procedure to select penalty parameter in $L_1$ penalized robust regression. This procedure is based on marginalization of prior distribution over the penalty parameter. Thus, resulting objective function does not include the penalty parameter due to marginalizing it out. In addition, its estimating algorithm automatically chooses a penalty parameter using the previous estimate of regression coefficients. The proposed approach bypasses cross validation as well as saves computing time. Variable-wise penalization also performs best in prediction and variable selection perspectives. Numerical studies using simulation data demonstrate the performance of our proposals. The proposed methods are applied to Boston housing data. Through simulation study and real data application we demonstrate that our proposals are competitive to or much better than cross-validation in prediction, variable selection, and computing time perspectives.

A Study on the Life Characteristic of Rodless Cylinder (로드리스 실린더의 수명 특성에 관한 연구)

  • Lee, C.S.;Lim, J.H.;Kang, S.B.
    • Journal of Drive and Control
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    • v.12 no.1
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    • pp.21-27
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    • 2015
  • Pneumatic cylinders are classified into rod-type pneumatic cylinders and rodless pneumatic cylinders depending on the presence of the rod. Rodless cylinders have a constant area and have no deflection. Rodless cylinders are widely used in automatic systems requiring high-speed performance and high-precision transportation. However, the research of the pneumatic cylinder has been focused on the structure and life characteristics. In this research, aging characteristics and shape parameter analysis which are related to the lifetime were investigated. By conducting the lifetime tests with two different materials for the transfer plate, the failure mode and lifetime characteristics were analyzed. By the Anderson-Darling (A-D) verification based on the complete data set, the analysis results of lifetime distribution, shape parameter, and scale parameter were provided.

A Study on Industrial Accident Cases by an Application of Correlation Analysis (상관분석을 응용한 산업재해 사례요인의 고찰)

  • 정국삼;홍광수
    • Journal of the Korean Society of Safety
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    • v.14 no.1
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    • pp.141-149
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    • 1999
  • At present time, industrial accidents statistics are used as the basic data of the policy to prevent industrial accidents and the plan to applicate the industrial accident insurance. But this statistical data is not sufficient for the effective safety management because it is the expression of the itemized distribution and the frequency for the whole cases. This study tried to correlational analysis for each causes by defining investigational items as their accident parameters. The correlational analysis, between the unsafe action and status and their relational causes, was performed to analyze the occurrence causes of industrial accident. And to assume the severity of accident, the correlativity and independency between causes and direct causes which are defined hospital days subordinate parameter were analyzed. In addition, this study expressed numerically the effectiveness of subordinate parameters depended on the level of independent parameter by presenting the predictive model between dependent parameter and independent parameter, which have the categorical parameter, through the Logit analysis method.

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An Approach to Walsh Functions for Parameter Estimation of Distributed Parameter Systems (WALSH함수의 접근에 의한 분포정수계의 파라메타 추정)

  • 안두수;배종일
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.7
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    • pp.740-748
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    • 1990
  • In this paper, we consider the problem of parameter estimation, i.e., definding the internal structure of a linear distribution parameter system from its input/output data. First, a linear partial differential equation describing the system is double-integrated with respect to two variables and then transformed into an integral equation. Next the Walsh Operation Matrix for Walsh function and their integration are introduced to transform the integral equation into algebraic simultaneous equations. Finally, we develop an algorithm to estimate the parameters of the linear distributed parameter system from the simple linear algebraic simultaneous equations. It is also shown that our algorithm could be effective in real time data processing since it uses the Fast Walsh Transform.

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Review of Parameter Estimation Procedure of Freund Bivariate Exponential Distribution (Freund 이변량 지수분포의 매개변수 추정과정 검토)

  • Park, Cheol-Soon;Yoo, Chul-Sang
    • Journal of Korea Water Resources Association
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    • v.45 no.2
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    • pp.191-201
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    • 2012
  • This study reviewed the parameter estimation procedure of the Freund bivariate exponential distribution for the decision of the annual maximum rainfall event. The method of moments was reviewed first, whose results were compared with those from the method of maximum likelihood. Both methods were applied to the hourly rainfall data of the Seoul rain gauge station measured from 1961 to 2010 to select the annual maximum rainfall events, which were also compared each other. The results derived are as follows. First, when applying the method of moments for the parameter estimation, it was found necessary to consider the correlation coefficient between the two variables as well as the mean and variance. Second, the method of maximum likelihood was better to reproduce the mean, but the method of moments was better to reproduce the annual variation of the variance. Third, The annual maximum rainfall events derived were very similar in both cases. Among differently selected annual maximum rainfall events, those with the higher rainfall amount were selected by the method of maximum likelihood, but those with the higher rainfall intensity by the method of moments.

Estimations in a skewed uniform distribution

  • Son, Hee-Ju;Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.4
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    • pp.733-740
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    • 2009
  • We obtain a skewed uniform distribution by a uniform distribution, and evaluate its coeffcient of skewness. And we obtain the approximate maximum likelihood estimator (AML) and moment estimator of skew parameter in the skewed uniform distribution. And we compare simulated mean squared errors (MSE) of those estimators, and also compare MSE of two proposed reliability estimators in two independent skewed uniform distributions each with different skew parameters.

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ON SIZE-BIASED POISSON DISTRIBUTION AND ITS USE IN ZERO-TRUNCATED CASES

  • Mir, Khurshid Ahmad
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.12 no.3
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    • pp.153-160
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    • 2008
  • A size-biased Poisson distribution is defined. Its characterization by using a recurrence relation for first order negative moment of the distribution is obtained. Different estimation methods for the parameter of the model are also discussed. R-Software has been used for making a comparison among the three different estimation methods.

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