• Communications for Statistical Applications and Methods
• /
• 제21권2호
• /
• pp.147-160
• /
• 2014

In this paper, we introduce the exponentiated Weibull-geometric (EWG) distribution which generalizes two-parameter exponentiated Weibull (EW) distribution introduced by Mudholkar et al. (1995). This proposed distribution is obtained by compounding the exponentiated Weibull with geometric distribution. We derive its cumulative distribution function (CDF), hazard function and the density of the order statistics and calculate expressions for its moments and the moments of the order statistics. The hazard function of the EWG distribution can be decreasing, increasing or bathtub-shaped among others. Also, we give expressions for the Renyi and Shannon entropies. The maximum likelihood estimation is obtained by using EM-algorithm (Dempster et al., 1977; McLachlan and Krishnan, 1997). We can obtain the Bayesian estimation by using Gibbs sampler with Metropolis-Hastings algorithm. Also, we give application with real data set to show the flexibility of the EWG distribution. Finally, summary and discussion are mentioned.

• Communications for Statistical Applications and Methods
• /
• 제10권1호
• /
• pp.1-9
• /
• 2003

In this article, we consider a Bayesian estimation method for the geometric mean of $textsc{k}$ exponential parameters, Using the Tibshirani's orthogonal parameterization, we suggest an invariant prior distribution of the $textsc{k}$ parameters. It is seen that the prior, probability matching prior, is better than the uniform prior in the sense of correct frequentist coverage probability of the posterior quantile. Then a weighted Monte Carlo method is developed to approximate the posterior distribution of the mean. The method is easily implemented and provides posterior mean and HPD(Highest Posterior Density) interval for the geometric mean. A simulation study is given to illustrates the efficiency of the method.

• International Journal of Reliability and Applications
• /
• 제9권1호
• /
• pp.31-52
• /
• 2008

In this paper generalized version of the geometric distribution is introduced. This distribution can be considered as a two-parameter generalization of the discrete geometric distribution. The main statistical and reliability properties of this distribution are discussed. Two methods of estimation, namely maximum likelihood method and the method of moments are used to estimate the parameters of this distribution. Simulation is utilized to calculate these estimates and to study some of their properties. Also, asymptotic confidence limits are established for the maximum likelihood estimates. Finally, the appropriateness of this new distribution for a set of real data, compared with the geometric distribution, is shown by using the likelihood ratio test and the Kolmogorove-Smirnove test.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제54권1호
• /
• pp.40-47
• /
• 2005

This paper concerns on Filtered-x least mean square (FXLMS) algorithm for adaptive estimation of feedforward control parameters. The conditions for convergence in ensemble mean of the FXLMS algorithm are derived and the directional convergence properties are discussed from a new geometric vector analysis. The convergence and its directionality are verified along with some computer simulations.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2009년도 추계학술대회 논문집
• /
• pp.11-12
• /
• 2009

• 한국생산제조학회지
• /
• 제21권2호
• /
• pp.208-213
• /
• 2012

In this paper, the radial error of a rotary table at five-axis machine tool is evaluated by utilizing ISO 230-2 and estimation method using double ball-bar. The geometric error of a rotary table is defined as position dependent geometric errors or position independent geometric errors according to their physical character. Then estimation method of geometric errors using double ball-bar is simply summarized including measurement path, parametric modeling and least squares approach. To estimate representative radial error, offset error, set-up error which affect to the double ball-bar data, mean value of measured data including CCW/CW-direction are used at estimation process. Radial errors are separated from measured data and used for evaluation with ISO 230-2. Finally, suggested evaluation method is applied to a rotary table at five-axis machine tool and its result is analyzed to improve the accuracy of the rotary table.

• 전자공학회논문지SC
• /
• 제45권3호
• /
• pp.20-31
• /
• 2008

본 논문에서는 단일 카메라를 이용하여 영상 내에 존재하는 객체의 3차원 공간 상에서의 위치 및 높이를 추출하기 위한 기법을 제안한다. 본 논문에서 제안하는 방법은 영상으로 사영된 3차원 장면(scene)에 대한 기준 좌표계를 마커(marker)를 이용해서 설정한 다음, 대상 물체의 2차원 영상을 기준 좌표계로 직접 역사영(back-projection) 시킴으로써 대상 물체에 대한 3차원 공간에서의 위치 및 높이를 계산한다. 그리고 부정확한 카메라 교정으로 인하여 발생하는 역사영 오차를 마커의 기하학 정보를 이용해서 보정한다. 제안된 방법은 기존의 방법에서 주로 이용되던 소실점(vanishing point) 및 소실선(vanishing line) 등을 이용하지 않으며, 3차원 공간 내에서의 객체의 높이 및 위치의 동시 추정이 가능한 장점이 있다. 또한 단일 카메라만을 이용하여 필요한 위치 및 높이 정보를 추출하기 때문에 다중 카메라를 이용한 기법에서 발생할 수 있는 3차원 좌표계 상에서의 대응점의 모호성, 다수의 카메라를 정확히 교정시켜야 하는 어려움 등의 문제가 발생하지 않는다. 실험 결과를 통하여 제안된 기법의 정확도 및 안정성을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.607-612
• /
• 1992

For hydroforming process, determination of back-up fluid pressure in chamber is one of the most essential tasks. In this paper, we present a back-up pressure estimation system which estimates the back-up pressure of hydroforming process utilizing a multi-layered neural network. The neural network learns the nonlinear relation ship between the back-up pressure and the geometric state variables of hydroforming process. The proposed method does not necessitate sophisticated analysis on hydroforming process but some geometric intuition. The experimental results show that the neural network well approximates the nonlinear relationship between the back-up pressure and the geometric state variables of hydroforming process, thus giving the good estimation of back-up pressure vs punch stroke curve.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집(한일합동학술편); 한국과학기술대학, 충남; 16-17 Oct. 1987
• /
• pp.932-938
• /
• 1987

The dynamic equations of robotic manipulators can be derived from either Newton-Euler equation or Lagrangian equation. Model parameters which appear in the resulting dynamic equation are the nonlinear functions of both the inertial parameters and the geometric parameters of robotic manipulators. The identification of the model parameters is important for advanced robot control. In the previous methods for the identification of the model parameters, the geometric parameters are required to be predetermined, or the robotic manipulators are required to follow some special motions. In this paper, we propose an approach to the identification of the model parameters, in which prior knowledge of the geometric parameters is not necessary. We show that the estimation equation for the model parameters can be formulated in an upper block triangular form. Utilizing the special structures, we obtain a simplified least-square estimation algorithm for the model parameter identification. To illustrate the practical use of our method, a 4DOF SCARA robot is examined.

• 한국생산제조학회지
• /
• 제24권4호
• /
• pp.386-393
• /
• 2015

A study is carried out on investigation on pattern costs, identification of geometric parameters for the cost, and development of cost estimation models for casting patterns. Pattern costs for machine tool structures are collected and analyzed to identify the important geometric parameters that affect the costs. The parameters are used for the development of the costing models. It is found that the geometric parameters can be easily obtained from a CAD system and then the costing models estimate a pattern cost in a minimum time. The models are verified with the structures whose pattern cost was used for this study. It is expected that this costing models can evaluate the cost of casting structures of machine tools in search of a near-optimal design based on manufacturing cost and, for example, weight at the design stage.