• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.627-630
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• 1999

For depth extraction from the focus and recovery the shape, determination of criterion function for focus measure and size of the criterion window are very important. However, Texture, illumination, and magnification have an effect on focus measure. For that reason, depth map has a partial high and low peak. In this paper, we propose a depth extraction method from focused images using the error interpolation. This method is modified the error depth into mean value between two normal depth in order to improve the depth map.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.78-87
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• 1996

In this paper, a remeshing criterion has been suggested in order to order to automate the remeshing decision during finite element analysis of metal forming. In order to use for the remeshing decision, two of remeshing criteria have been investigated. One is the use of error estimates based on errors in stresses and strain rate of the finite element solution and the other is the use of geometric characterisreics of distorted elements. As a result, the strain rate error estimate in power norm based on the former is found to give more valuable information about remeshing decision than the ones based on the latter. Examples are given to demon- strate the usefulness of the suggested eroor estimate as a remeshing criterion.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.247-250
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• 2001

In this paper, we propose an growing and pruning algorithm to design the adaptive structure of modular wavelet neural network(MWNN) with F-projection and geometric growing criterion. Geometric growing criterion consists of estimated error criterion considering local error and angle criterion which attempts to assign wavelet function that is nearly orthogonal to all other existing wavelet functions. These criteria provide a methodology that a network designer can constructs wavelet neural network according to one's intention. The proposed growing algorithm grows the module and the size of modules. Also, the pruning algorithm eliminates unnecessary node of module or module from constructed MWNN to overcome the problem due to localized characteristic of wavelet neural network which is used to modules of MWNN. We apply the proposed constructing algorithm of the adaptive structure of MWNN to approximation problems of 1-D function and 2-D function, and evaluate the effectiveness of the proposed algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.87-95
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• 2009

As information theoretic learning techniques, error entropy minimization criterion (MEE) and maximum cross correntropy criterion (MCC) have been studied in depth for supervised learning. MEE criterion leads to maximization of information potential and MCC criterion leads to maximization of cross correlation between output and input random processes. The weighted combination scheme of these two criteria, namely, minimization of Error Entropy with Fiducial points (MEEF) has been introduced and developed by many researchers. As an approach to unsupervised, blind channel equalization, we investigate the possibility of applying constant modulus error (CME) to MEE criterion and some problems of the method. Also we study on the application of CME to MEEF for blind equalization and find out that MEE-CME loses the information of the constant modulus. This leads MEE-CME and MEEF-CME not to converge or to converge slower than other algorithms dependent on the constant modulus.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.773-779
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• 2015

We study a statistical analysis about the fifth wave data of the Korea National Health and Nutrition Examination Survey based on linear regression models with measurement errors. The data is obtained from a national population-based complex survey. To demonstrate the availability of measurement error models, two results between the general linear regression model and measurement error model are compared based on the model selection criteria which are Akaike information criterion and Bayesian information criterion. For our study, we use the simulation extrapolation algorithm for measurement error model and the jackknife method for the estimation of standard errors.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.303-309
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• 1993

In this paper we have defined two approaches to be error-robust when the precise form of error-structure is unknown. An experiment is optimal by the first criterion if it maximizes the minimum effciency over all candidates of error structure and is optimal by the second if it maximizes the minimum average of the efficiency over all candidates of error structure. In order to appreciate the basic implications of each design criterion, these approaches are applied to two different experimental situations, D- and heteroscedastic G-optimalities.

• Journal of the Korean Statistical Society
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• v.20 no.2
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• pp.147-155
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• 1991

This paper treats a robust design criterion which minimizes the effects of outliers and model inadequacy, and investigates robust designs for some response surface designs. In order to develop a robust design criterion and robust design, the integrated mean squared error of *(equation omitted) over a region is utilized, where *(equation omitted). is the estimated response by the minimum bias estimation proposed by carson, Manson and Hader (1969) . According to the number of aberrant observations and their positions, the proposed criterion and designs are studied. Also further development of the proposed criterion is treated when outliers can occur in any position of a design.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.449-453
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• 2001

In this paper, we propose an algorithm to design the adaptive structure of wavelet neural network with F-projection and geometric growing criterion. Geometric growing criterion consists of estimated error criterion considering local error and angle criterion which attempts to assign a wavelet function that is nearly orthogonal to all other existing wavelet functions. These criteria provide a methodology that a network designer can construct wavelet neural network according to one's intention. We apply the proposed constructing algorithm of the adaptive structure of wavelet neural network to approximation problems of 1-D and 2-D function, and evaluate the effectiveness of the proposed algorithm.

• Tunnel and Underground Space
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• v.21 no.5
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• pp.349-358
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• 2011

This paper introduces a new P wave arrival time determination algorithm of acoustic emission (AE) suitable to identify P waves with low signal-to-noise ratio generated in rock masses around the high-level radioactive waste disposal repositories. The algorithms adopted for this paper were amplitude threshold picker, Akaike Information Criterion (AIC), two step AIC, and Hinkley criterion. The elastic waves were generated by Pencil Lead Break test on a granite sample, then mixed with white noise to make it difficult to distinguish P wave artificially. The results obtained from amplitude threshold picker, AIC, and Hinkley criterion produced relatively large error due to the low signal-to-noise ratio. On the other hand, two step AIC algorithm provided the correct results regardless of white noise so that the accuracy of source localization was more improved and could be satisfied with the error range.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.624-634
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• 1994

A numerical method which combines equal-order velocity-pressure formulation originated from SIMPLE algorithm and streamline upwinding method has been developed. To verify the proposed numerical method, we considered the lid-driven cavity flow and backward facing step flow. The trend of convergence history is stable up to the error criterion beyond which the maximum value of error is oscillatory due4 to the round-off error. In the present study, all results were obtained with the single precision calculation up to the given error criterion and it was found to be sufficient for our purpose. The present results were then compared with existing experimental results using laser doppler velocimetry and numerical results using finite difference method and mixed interpolation finite element method. It has been shown that the present method gives accurate results with less memories and execution time than the coventional finite element method.