• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2355-2358
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• 2000

This paper presents signal analyzer design, realization of system parameter estimation, analysis and system parameter estimation of distributed parameter systems using orthogonal function like Walsh function, block pulse function and Haar function.

• Bulletin of the Korean Mathematical Society
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• v.57 no.3
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• pp.751-762
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• 2020

We define the average of a set of continuous functions of two variables (surfaces) using the structure of the two-parameter Wiener space that constitutes a probability space. The average of a sample set in the two-parameter Wiener space is defined employing the two-parameter Wiener process, which provides the concept of distribution over the two-parameter Wiener space. The average defined in our work, called an average function, also turns out to be a continuous function which is very desirable. It is proved that the average function also lies within the range of the sample set. The average function can be applied to model 3D shapes, which are regarded as their boundaries (surfaces), and serve as the average shape of them.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.601-608
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• 2007

Lee, et al. (1999) proposed a unique but universal robust objective function replacing the square objective function for the radial basis function network, and demonstrated some advantages. In this article, the robust objective function in Lee, et al. (1999) is adapted for a multilayer perceptron (MLP). The shape of the robust objective function is formed by the scale parameter. Another method of determining a proper value of that parameter is proposed.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.33-55
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• 2007

The economic world is full of patterns, many of which exert a profound influence over society and business. One of the most contentious is the distribution of wealth. Way back in 1897, an Italian engineer-turned-economist named Vilfredo Pareto discovered a pattern in the distribution of wealth that appears to be every bit as universal as the laws of thermodynamics or chemistry. The present paper proposes some Bayes estimators of shape parameter of Pareto income distribution in censored sampling. Asymmetric LINEX loss function has been considered to study the effects of overestimation and underestimation. For the prior distribution of the parameter involved a number of priors including one and two-parameter exponential, truncated Erlang and doubly truncated gamma have been contemplated to express the belief of the experimenter s/he has regarding the parameter. The estimators thus obtained have been compared theoretically and empirically with the corresponding estimators under squared error loss function, some of which were reported by Bhattacharya et al. (1999).

• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.597-605
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• 2010

This paper presents a contribution to parameter identification of a non-linear system using a new strategy to improve the genetic algorithm (GA) method. Since cost function plays an important role in GA-based parameter identification, we propose to improve the simple version of GA, where weights of the cost function are not taken as constant values, but varying along the procedure of parameter identification. This modified version of GA is applied to the induction motor (IM) as an example of nonlinear system. The GA cost function is the weighted sum of stator current and rotor speed errors between the plant and the model of induction motor. Simulation results show that the identification method based on improved GA is feasible and gives high precision.

• Journal of applied mathematics & informatics
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• v.10 no.1_2
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• pp.309-323
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• 2002

This paper studies the parameter estimation problem for a steady state flow in an inhomogeneous medium. Our approximation scheme could be used when the diffusion coefficient is singular. The function space parameter estimation convergence(FSPEC) is considered and numerical simulations are performed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.8
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• pp.792-804
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• 1990

This paper describes an efficient optimization algorithm by calculating sensitivity function for power system stabilization. In power system, the dynamic performance of exciter, governor etc. following a disturbance can be presented by a nonlinear differential equation. Since a nonlinear equation can be linearized for small disturbances, the state equation is expressed by a system matrix with system parameters. The objective function for power system operation will be related to the system parameter and the initial state at the optimal control condition for control or stabilization. The object function sensitivity to the system parameter can be considered to be effective in selecting the optimal parameter of the system.

• Structural Engineering and Mechanics
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• v.22 no.4
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• pp.401-418
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• 2006

Solutions to the problems of structural parameter estimation from modal response using leastsquares minimization of force or displacement residuals are generally sensitive to noise in the response measurements. The sensitivity of the parameter estimates is governed by the physical characteristics of the structure and certain features of the noisy measurements. It has been shown that the regularization method can be used to reduce effects of the measurement noise on the estimation error through adding a regularization function to the parameter estimation objective function. In this paper, we adopt the regularization function as the Euclidean norm of the difference between the values of the currently estimated parameters and the a priori parameter estimates. The effect of the regularization function on the outcome of parameter estimation is determined by a regularization factor. Based on a singular value decomposition of the sensitivity matrix of the structural response, it is shown that the optimal regularization factor is obtained by using the maximum singular value of the sensitivity matrix. This selection exhibits the condition where the effect of the a priori estimates on the solutions to the parameter estimation problem is minimal. The performance of the proposed algorithm is investigated in comparison with certain algorithms selected from the literature by using a numerical example.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.2
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• pp.97-108
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• 2008

In this paper Bayes estimator of the parameter and reliability function of the zero-truncated Poisson distribution are obtained. Furthermore, recurrence relations for the estimator of the parameter are also derived. Monte Carlo simulation technique has been made for comparing the Bayes estimator and reliability function with the corresponding maximum likelihood estimator (MLE) of zero-truncated Poisson distribution.

• Nonlinear Functional Analysis and Applications
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• v.29 no.1
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• pp.99-111
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• 2024

In this paper, a new seven-parameter Mittag-Leffler function of a single complex variable is proposed as a generalization of the standard Mittag-Leffler function, certain generalizations of Mittag-Leffler function, hypergeometric function and confluent hypergeometric function. Certain essential analytic properties are mainly discussed, such as radius of convergence, order, type, differentiation, Mellin-Barnes integral representation and Euler transform in the complex plane. Its relation to Fox-Wright function and H-function is also developed.