• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.785-787
• /
• 1999

In this paper, recursive least square algorithm is presented to estimate the parameters of step motor under low-speed operation. Parameter estimation is important for compensating the input current by calculating the ratio of the motor torque constant and detent torque constant that causes torque-ripple in low-speed applications. On-line parameter estimation process is a preliminary procedure to apply step motor to adaptive control. Computer simulation shows that the estimated parameters converge in finite time.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.1 no.1
• /
• pp.83-104
• /
• 1997

This paper studies parameter estimation for a first-order hyperbolic integro-differential equation modelling one-sex population dynamics. A second-order finite difference scheme is used to estimate parameters such as the age-specific death-rate and the age-specific fertility from fully discrete observations on the population. The function space parameter estimation convergence of this scheme is proved. Also, numerical simulations are performed.

• The Korean Journal of Applied Statistics
• /
• v.24 no.1
• /
• pp.177-183
• /
• 2011

Hidden Markov random eld(HMRF) is one of the most common model for image segmentation which is an important preprocessing in many imaging devices. The HMRF has unknown hyper-parameters on Markov random field to be estimated in segmenting testing images. However, in practice, due to computational complexity, it is often assumed to be a fixed constant. In this paper, we numerically show that the segmentation results very depending on the fixed hyper-parameter, and, if the parameter is misspecified, they further depend on the choice of the class-labelling algorithm. In contrast, the HMRF with estimated hyper-parameter provides consistent segmentation results regardless of the choice of class labelling and the estimation method. Thus, we recommend practitioners estimate the hyper-parameter even though it is computationally complex.

• Communications of the Korean Mathematical Society
• /
• v.33 no.4
• /
• pp.1367-1376
• /
• 2018

In practice, the density function of a random variable X is always unknown. Even its smoothness parameter is unknown to us. In this paper, we will consider a density smoothness parameter estimation problem via wavelet theory. The smoothness parameter is defined in the sense of equivalent Besov norms. It is well-known that it is almost impossible to estimate this kind of parameter in general case. But it becomes possible when we add some conditions (to our proof, we can not remove them) to the density function. Besides, the density function contains impurities. It is covered by some additive noises, which is the key point we want to show in this paper.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.51 no.2
• /
• pp.92-98
• /
• 2002

It is necessary to measure the solar cell parameter fur understanding characteristic of solar cell and applying to many other fields. Since photovoltaic system consists of solar cell module, which are connected each other in series and parallel, it is not proper to apply a solar cell parameter to photovoltaic system. Therefore, to estimate the solar tell module and to solve the problem of the established algorithm is on demand. In this paper the authors have improved the accuracy of solar cell module Parameter estimation by compensating series and Parallel resistance, and developed a new parameter estimation algorithm, which can be applied to photovoltaic system without high cost measuring equipment. And the validity of proposed algorithm is verified by the simulation and experimentation.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.5
• /
• pp.927-934
• /
• 2010

In this paper, we introduce a method of parameter estimation of progressive Type I interval censored sample and progressive type II censored sample. We propose a new parameter estimation method, that is converting the data which obtained by progressive type I interval censored, those data be used to estimate of the parameter in progressive type II censored sample. We used exponential distribution with unknown scale parameter, the maximum likelihood estimator of the parameter calculates from the two methods. A simulation is conducted to compare two kinds of methods, it is found that the proposed method obtains a better estimate than progressive Type I interval censoring method in terms of mean square error.

• Communications for Statistical Applications and Methods
• /
• v.10 no.2
• /
• pp.341-352
• /
• 2003

Collecting data through experiment, the observers are an import source of measurement error and the inference on the measure of agreement, say kappa, is necessary. The models commonly used are complicated general mixture model, which have many nuisance parameters. Orthogonalization of parameters reduce the effect of nuisance parameter. Orthogonalization of estimating function gives the same effect as the parameter orthogonalization. In this study, the method for orthogonalization of estimating equation is studied and applied to the Beta-binomial model to examine the properties of the estimate of kappa. As a result, the likelihood function is insensitive to the change of the nuisance parameter and bias is smaller than the result of m.1.e. when kappa has extreme values

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.9
• /
• pp.451-458
• /
• 2000

This paper addresses the issues of the parameter error detection and identification in electric power systems. In this paper, the parameter error identification and estimation is carried out as part of the state estimation. A two stage estimation procedure is used to detect and identify the parameter errors. The suspected parameters are identified by the WLAV state estimator as the first stage. A new WLAV state estimator adding the suspected system parameters in the state vector is used to estimate the exact value of parameter errors. Supporting examples are given by using IEEE 14 bus system.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.10
• /
• pp.1183-1189
• /
• 1999

This paper presents the method of parameter estimation of diffusion model for monitoring Demand-Side Management program. Bass diffusion model was applied in this paper, which has different values according to the following parameters; coefficients of innovation, imitation and potential adopters. Though it is very important to estimate three parameters precisely, there has been no empirical way in practice. Thus, this paper presents the method of parameter estimation in case of few data with constraints to reduce the possibility of bad estimation. The constraints can be empirical results or expert's decision. Case studies show the diffusion curves and forecasted values of the peak for the high-efficient lighting. The feedback and nonlinear least-square parameter estimation methods used in this paper enable us to evaluate the status and to predict the effect of DSM program.

• Journal of Environmental Science International
• /
• v.5 no.6
• /
• pp.727-738
• /
• 1996

An one dimensional atmosphere-canopy-soil interaction model is developed to estimate of the heat budget parameter in the atmospheric boundary layer. The canopy model is composed of the three balance equations of energy, temperature, moisture at ground surface and canopy layer with three independent variables of Tf(foliage temperature), Tg(ground temperature), and qg(ground specific humidity). The model was verilied by comparative study with OSUID(Oregon State University One Dimensional Model) proved in HAPEX-MOBILHY experiment. Also we applied this model in two dimensional land-sea breeze circulation. According to the results of this study, surface characteristics considering canopy acted importantly upon the simulation of meso-scale circulation. The factors which used in the numerical experiment are as follows ; the change for a sort of soil(sand and peat), the change for shielding factor, and the change for a kind of vegetation.