• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.39-74
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• 2018

Purpose: For more than 30 years, robust parameter design (RPD), which attempts to minimize the process bias (i.e., deviation between the mean and the target) and its variability simultaneously, has received consistent attention from researchers in academia and industry. Based on Taguchi's philosophy, a number of RPD methodologies have been developed to improve the quality of products and processes. The primary purpose of this paper is to review and discuss existing RPD methodologies in terms of the three sequential RPD procedures of experimental design, parameter estimation, and optimization. Methods: This literature study composes three review aspects including experimental design, estimation modeling, and optimization methods. Results: To analyze the benefits and weaknesses of conventional RPD methods and investigate the requirements of future research, we first analyze a variety of experimental formats associated with input control and noise factors, output responses and replication, and estimation approaches. Secondly, existing estimation methods are categorized according to their implementation of least-squares, maximum likelihood estimation, generalized linear models, Bayesian techniques, or the response surface methodology. Thirdly, optimization models for single and multiple responses problems are analyzed within their historical and functional framework. Conclusion: This study identifies the current RPD foundations and unresolved problems, including ample discussion of further directions of study.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.112-118
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• 2000

This paper deals with the application of sensitivity method to the parameter estimation for the dynamic analysis of gener-al mechanical system. In this procedure we take the derivatives of the given system with respect to a certain parameter and use this information to implement the steepest descent method. This paper will give two examples of this technique applied to simple vehicle models. This paper will give two examples of this technique applied to simple vehicle models. Simulation results show excellent convergence and accuracy of parameter estimates.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

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

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.59-64
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• 2011

In this paper, the lumped element model parameter estimation method and its implemented estimation software for fabricated floating mass transducers of IMEHDs have been presented so that the estimated parameter values could be compared with the designed ones and applied to predict the output performance when the transducers were implanted into human ears. The presented method is based on the sequential quadratic programming (SQP) for estimating parameters in the transducer's lumped model and has been implemented by the use of LabVIEW graphical language. Using the implemented estimation software, the accuracy of parameter estimation has been verified and our implemented estimation method has been evaluated by the comparison of the estimated transducer parameter values with the designed ones for a practically fabricated floating mass transducer for IMEHDs.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1984.04a
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• pp.42-45
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• 1984

we propose a new parameter estimation algorithm that converge with probability one and in mean square, If the mean is the function of parameter of the probability density function. This recursive algorithm is applicable also ever the parameters we estimate are multiparameter case. And the results are shown by the computer simulation.

• 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.

• Journal of Mechanical Science and Technology
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• v.20 no.8
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• pp.1224-1231
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• 2006

The stability and control derivatives of DURUMI-lI UAV using the flight test are obtained. The flight test data is gathered from the normal flight condition (normal mode) and the flight condition assumed as the right elevator fixed (fault mode). Using real-time parameter estimation techniques, applied to Fourier transform regression method, simulates the aircraft motion. From the result, the fault of control surface is to be detected. In this paper, the results of the real- time parameter estimation techniques are compared with the results of the Advanced Aircraft Analysis (AAA). Using the aerodynamic derivatives, it provides the base line of normal/failure for the control surface by using the on-line parameter estimation of Fourier transform regression. In flight, this approach maybe helpful to detect and isolate the fault of primary control surface. It is explained how to perform the flight condition assumed as the right elevator fixed in the flight test. Also, it is mentioned how to switch between the normal flight condition and the assumed fault flight condition.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.271-276
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• 1997

A dynamic discount approach is proposed for the estimation of the Poisson parameter and the forecasting of the Poisson random variable, where the parameter of the Poisson distribution varies over time intervals. The recursive estimation procedure of the Poisson parameter is provided. Also the forecasted distribution of the Poisson random variable in the next time interval based on the information gathered until the current time interval is provided.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1209-1217
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• 2006

For the mixture of shifted Poisson distributions, a method of parameter estimation is proposed. The range of the shifted parameters are estimated first and for each shifted parameter set EM algorithm is applied to estimate the other parameters of the distribution. Among the estimated parameter sets, one with minimum likelihood for given data is to be set as the final estimate. In simulation experiments, the suggested estimation method shows to have a good performance.