• Transactions of Materials Processing
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• v.4 no.1
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• pp.92-104
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• 1995

It often happens some elements are so largely distorted during a large-deformation finite element analysis that further calculation becomes impossible or the approximation error increases rapidly. This problem can be overcomed only by remeshing at several suitable stages. The present study aimed to establish the criterion based on the error estimators, and examined in the simulation and posterior error analysis of ring compression test to demonstrate the usefulness of them. The distribution of each error estimator and its variation during deformation were investigated. All the error estimators were increased monotonously with deformation and decreased rapidly at remeshing stage. It was shown that the error estimators suggested in this study are good measures as remeshing criterion for large deformation finite element analyses.

• The Journal of the Acoustical Society of Korea
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• v.16 no.3E
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• pp.62-68
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• 1997

In this paper, a modified adaptive sign (MAS) algorithm based on a mixed norm error criterion is proposed. The mixed norm error criterion of be minimized is constructed as a combined convex function of the mean-absolute error and the mean-absolute error to the third power. A convergence analysis of the MAS algorithm is also presented. Under a set of mild assumptions, a set of nonlinear evolution equations that characterizes the statistical mean and mean-squared behavior of the algorithm is derived. Computed simulations are carried out to verify the validity of our derivations.

• Journal of Internet Computing and Services
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• v.14 no.1
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• pp.9-14
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• 2013

The criterion of zero-error probability provides a limitation on error probability functions being used for adaptive systems when the error samples are shifted by the influence of DC-bias noise. In this paper, we employ a bias term in the error distribution and propose a new criterion of the biased zero-error probability with error being zero. Also, by maximizing the proposed criterion on expanded filter structures, a supervised adaptive algorithm has been derived. From the simulation results of supervised equalization, the algorithm based on the proposed criterion yielded zero-centered and highly concentrated error samples without disturbance in the environments of strong impulsive and DC-bias noise.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.5 no.3
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• pp.80-85
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• 2006

In an effort to reduce the evaluation time of the precision of manufactured disk cams, an effective measuring method with an exclusively built profile-measuring machine and subsequent data analysis procedure is proposed. The design and measuring data are interpolated by cubic spline curves to compute the precision error which is defined by the maximum and minimum distances between two curves. The minimum zone criterion of ISO is employed to evaluate the form error, and genetic algorithm is used to search the orientation and location of design data for the measured data which minimizes the form error. The proposed system was applied to marine engine cams, and it shows that the form error is reduced to 30% down compared with the method which minimizes the form error with the assumption that the centers of measured data design cam curve are identical.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.621-624
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• 2011

With the rapid growth of internet traffic, accurate and reliable prediction of internet traffic has been a key issue in network management and planning. This paper proposes an autoregressive-generalized autoregressive conditional heteroscedasticity (AR-GARCH) error model for forecasting internet traffic and evaluates its performance by comparing it with seasonal autoregressive integrated moving average (ARIMA) models in terms of root mean square error (RMSE) criterion. The results indicated that the seasonal AR-GARCH models outperformed the seasonal ARIMA models in terms of forecasting accuracy with respect to the RMSE criterion.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.19-26
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• 2009

In this paper, a minimum Euclidian distance criterion between error PDF and Dirac delta function is introduced and a constant modulus type blind equalizer algorithm based on the criterion is proposed. The proposed algorithm using constant modulus error in place of actual error term of the criterion has superior convergence and steady state MSE performance, and the error signal of the proposed algorithm exhibits more concentrated density function in blind equalization environments. Simulation results indicate that the proposed method can be a reliable candidate for blind equalizer algorithms for multipoint communications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1865-1870
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• 2015

In signal processing, the zero-error probability (ZEP) criterion and related algorithm (MZEP) outperforms MSE-based algorithms and yields superior and stable convergence in impulsive noise environment. In this paper, the analysis of the relationship with MSE criterion proves that ZEP criterion has equivalent optimum solution of MSE criterion. Also this work reveals that the magnitude controlled input of MZEP algorithm plays the role in keeping the optimum solution undisturbed from impulsive noise.

• Journal of the Korean Data and Information Science Society
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• v.19 no.1
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• pp.25-36
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• 2008

Error Correcting Output Codes (ECOC) can improve generalization performance when applied to multicategory classification problem. In this study we propose a new criterion to select hyperparameters included in ECOC scheme. Instead of margins of a data we propose to use the probability of misclassification error since it makes the criterion simple. Using this we obtain an upper bound of leave-one-out error of OVA(one vs all) method. Our experiments from real and synthetic data indicate that the bound leads to good estimates of parameters.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.1
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• pp.39-46
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• 1993

In developing a multiple regression relationship, independent variables are frequently measured with error. For these situations the problem of estimating unknown parameters has been extensively discussed in the literature while little attention has been given to the prediction problem. In this paper a criterion is developed for assessing the severeness of measurement errors in each independent variable on the predicted values. Using the developed criterion we can present a guideline as to which measurement error should be controlled for a more accurate prediction. Proposed methods are illustrated with a standard data system in work measurement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.