• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06a
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• pp.71-75
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• 1998

압축된 비디오 신호를 전송함에 있어 에러에 의해 영상이 손상되는 영향을 최소화하기 위하여 여러 가지 오류은닉 기법들이 제안되고 있다. 본 논문에서는 인터 프레임에서 오류가 발생하여 정보가 손실되었을 경우, 움직임벡터의 효율적인 복구를 통한 오류은닉 방식을 제안하였다. 이를 위해 기존의 블록오류은닉 방식이 갖고 있는 문제점들을 살펴보고 이 중 전체 합 문제(total sum problem)에 대해 해결책으로 제시 될 수 있는 Infinite Norm을 이용한 블록경계정합방식을 제안하였고 실험에 의해 그 성능을 검증하였다.

• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.1-10
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• 1998

In the problem of estimating a vector of unknown regression coefficients under the sum of squared error losses in a hierarchical linear model, we propose the hierarchical Bayes estimator of a vector of unknown regression coefficients in a hierarchical linear model, and then prove the admissibility of this estimator using Blyth's (196\51) method.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.163-172
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• 1999

We propose a cross-validatory method for the choice of the number of principal components in principal component regression based on the magnitudes of correlations with y. There are two different manners in choosing principal components, one is the order of eigenvalues(Shin and Moon, 1997) and the other is that of correlations with y. We apply our method to various data sets and compare results of those two methods.

• The Journal of the Acoustical Society of Korea
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• v.18 no.2E
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• pp.3-9
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• 1999

In this paper we study the convergence behavior of the least mean fourth(LMF) algorithm where the error raised to the power of four is minimized for a multiple sinusoidal input and Gaussian measurement noise. Here we newly obtain the convergence equation for the sum of the mean of the squared weight errors, which indicates that the transient behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant. It should be noted that no similar results can be expected from the previous analysis by Walach and Widrow/sup [1]/.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.205-216
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• 1996

Consider the problem of estimating a multivariate normal mean with an unknown covarience matrix under a weighted sum of squared error losses. We first provide hierarchical Bayes estimators which shrink the usual (maximum liklihood, uniformly minimum variance unbiased) estimator towards a regression surface and then prove the admissibility of these estimators using Blyth's (1951) method.

• Journal of the Korean Geophysical Society
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• v.5 no.2
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• pp.131-142
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• 2002

Geomagnetic transfer function is generally estimated by choosing transfer to minimize the square sum of differences between observed values. If the error structure sccords to the Gaussian distribution, standard least square(LS) can be the estimation. However, for non-Gaussian error distribution, the LS estimation can be severely biased and distorted. In this paper, the Gaussian error assumption was tested by Q-Q(Quantile-Quantile) plot which provided information of real error structure. Therefore, robust estimation such as regression M-estimate that does not allow a few bad points to dominate the estimate was applied for error structure with non-Gaussian distribution. The results indicate that the performance of robust estimation is similar to the one of LS estimation for Gaussian error distribution, whereas the robust estimation yields more reliable and smooth transfer function estimates than standard LS for non-Gaussian error distribution.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.5
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• pp.1104-1111
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• 1990

A method to identify nonlinear elements position of a nonlinear system is presented. Nonlinear elements position can be identified by an equivalent error damping and stiffness matrices which are based on the equivalent linearization technique. The procedures of this technique are: (1) Obtain input force and system response. (2) Define error between the actual and linearized restoring forces. (3) Calculate linearized damping and stiffness coefficients to minimize the square error sum. Several examples are tested and found that these methods are very effective not only to locate the nonlinear elements position but also to identify the degree of nonlinearity qualitatively. Nonlinear type can be qualitatively identified by examining the plots of restoring force vs equivalent state values.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.205-215
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• 2012

A GPS sensor is widely used in many areas such as navigation, or air traffic control. Particularly, the car navigation system is equipped with GPS sensor for locational information. However, when a car goes through a tunnel, forest, or built-up area, GPS receiver cannot get the enough number of satellite signals. In these situations, a GPS receiver does not reliably work. A GPS error can be formulated by sum of bias error and sensor noise. The bias error is generated by the geometric arrangement of satellites and sensor noise error is generated by the corrupted signal noise of receiver. To enhance GPS sensor accuracy, these two kinds of errors have to be removed. In this research, we make the road database which includes Road Database File (RDF). RDF includes road information such as road connection, road condition, coordinates of roads, lanes, and stop lines. Among the information, we use the stop line coordinates as a feature point to correct the GPS bias error. If the relative distance and angle of a stop line from a car are detected and the detected stop line can be associated with one of the stop lines in the database, we can measure the bias error and correct the car's location. To remove the other GPS error, sensor noise, the Kalman filter algorithm is used. Additionally, using the RDF, we can get the information of the road where the car belongs. It can be used to help the GPS correction algorithm or to give useful information to users.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.209-216
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• 1996

In this paper, we propose a learning method of multi-layer perceptrons (MLPs) with 8-bit data precision. The suggested method uses the cross-entropy cost function to remove the slope term of error signal in output layer. To decrease the possibility of overflows, we use 16-bit weighted sum results into the 8-bit data with appropriate range. In the forwared propagation, the range for bit-conversion is determined using the saturation property of sigmoid function. In the backwared propagation, the range for bit-conversion is derived using the probability density function of back-propagated signal. In a simulation study to classify hadwritten digits in the CEDAR database, our method shows similar generalization performance to the error back-propagation learning with 16-bit precision.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.378-386
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• 2002

Multi-path ultrasonic Sow measurement system uncertainty is determined by assigning an expected error of each component of flow measurement and then defining the total flow measurement uncertainty as square root of the sum of squared values of the individual error. Sources of uncertainty for flow measurement are geometry, transit time and velocity profile integration uncertainty. A theoretical uncertainty model for multi-path ultrasonic transit time flowmeter configured with parallel 5 chords, is derived from and calculated by dry calibration method.