• 한국통신학회논문지
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• 제35권8A호
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• pp.760-767
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• 2010

For complex channel blind equalization, this study presents the performance and characteristics of two complex blind information theoretic learning algorithms (ITL) which are based on minimization of Euclidian distance (ED) between probability density functions compared to constant modulus algorithm which is based on mean squared error (MSE) criterion. The complex-valued ED algorithm employing constant modulus error and the complex-valued ED algorithm using a self-generated symbol set are analyzed to have the fact that the cost function of the latter forces the output signal to have correct symbol values and compensate amplitude and phase distortion simultaneously without any phase compensation process. Simulation results through MSE convergence and constellation comparison for severely distorted complex channels show significantly enhanced performance of symbol-point concentration with no phase rotation.

• ETRI Journal
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• 제39권1호
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• pp.13-20
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• 2017

A method is proposed for scheduling sensor accesses to the shared network in a networked control system. The proposed method determines the access order in which the sensors are granted medium access through minimization of the state estimation error covariance. Solving the problem by evaluating the error covariance for each possible ordered set of sensors is not practical for large systems. Therefore, a convex optimization problem is proposed, which yields approximate yet acceptable results. A state estimator is designed for the augmented system resulting from the incorporation of the optimally chosen communication sequence in the plant dynamics. A car suspension system simulation is conducted to test the proposed method. The results show promising improvement in the state estimation performance by reducing the estimation error norm compared to round-robin scheduling.

• 한국정밀공학회지
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• 제3권1호
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• pp.29-39
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• 1986

An adaptive controller which is robust to the unknown load disturbance is developed for electro-hydraulic speed control systems. Since the load disturbance degrades the performance of the controller such as a steady state error and rise time in the conventional control system, appropriate adjustment of the controller is necessary in order to obtain the desired performances. The adaptation mechanism was designed to tune the feedforward gain, based upon minimization of ITAE (integral of time-multiplied absolute error) performance. The unknown load distrubance was identified by using an analog computer from the relationship between the velocity of the hydraulic motor and the load pressure. To evaluate the performance of the controller a series of simulations and experiments were conducted for various load conditions. Both results show that the proposed adaptive controller shows abetter performance than the conventional controller in terms of the steady state error and rise time.

• The Journal of the Acoustical Society of Korea
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• 제13권1E호
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• pp.64-70
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• 1994

예측신경회로망 모델은 패턴 예측에 의한 매우 효과적인 음성인식 모델이다. 그러나, 그러한 모델은 유사한 어휘간에서 변별력이 떨어지는 단점이 있다. 이 논문에서는 그러한 단점을 극복하기 위한 변별력있는 학습 알고리즘을 제안한다. 이 알고리즘은 최소 분류 오차 수식화와 GPD 알고리즘으로부터 유도외면 그에 따라서 인식 오차의 수를 직접 최소화하는 것이 가능하다. 한국어 숫자음에 대한 인식 실험결과, 기존의 알고리즘에서 발생하는 오인식의 30%를 줄일 수 있었다.

• 품질경영학회지
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• 제33권1호
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• pp.73-82
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• 2005

This article proposes a practical approach, which is based on the concept of the expected squared relative error, that can consider both the prediction quality and the practitioner's subjectivity in simultaneously optimizing multiple responses. Through a case study, multiresponse optimization using the expected squared relative error approach is illustrated, and the SAS program to implement the proposed method is provided.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (B)
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• pp.715-717
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• 2004

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on a recursive error back-projection of top-down machine learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes, In addition to, a recursive error back-projection is applied to improve the accuracy of synthesized high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution one captured at a distance.

• 응용통계연구
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• 제22권2호
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• pp.403-414
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• 2009

국내외적으로 지역통계에 관한 관심이 높아지고 있으며 이와 관련하여 소지역 추정에 관한 많은 연구가 진행되고 있다. 소지역 추정에 사용되는 추정량의 대부분은 MSE(moan squared error)를 최소화하여 얻어진다 (Rao, 2003). 최근 황희진과 신기일 (2008)은 MSPE(mean squared percentage error)를 최소화하는 추정량을 사용한 소지역 추정법을 제안하였다. 본 논문에서는 노동통계 중 지청별 일인당 평균 임금총액 추정에 황희진과 신기일 (2008)이 제안한 방법을 적용하여 보았으며 2007년 매월 노동통계 자료를 이용하여 기존의 MSE를 최소화 하여 얻어진 여러 추정량과 우수성을 비교해 보았다. 또한 노동통계를 위 한 소지역 추정의 실제 사용 가능성을 살펴보았다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.366-369
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• 1991

Load shedding algorithm has been developed using heuristic search and D.C flow method. The line flow error with a D.C method was improved in this paper. Minimization of load shedding was obtained with heuristic search method. Although analytical method have been mixed with expert algorithm the C language fitted well for this purpose.

• 한국정보통신학회논문지
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• 제9권7호
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• pp.1569-1574
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• 2005

In this paper, I propose an intelligent credit rating system using a bankruptcy prediction model based on support vector machines (SVMs). SVMs are promising methods because they use a risk function consisting of the empirical error and a regularized term which is derived from the structural risk minimization principle. This study examines the feasibility of applying SVM in Predicting corporate bankruptcies by comparing it with other data mining techniques. In addition. this study presents architecture and prototype of intelligeht credit rating systems based on SVM models.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1169-1172
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• 1996

A time-optimal control law for quick, strongly nonlinear systems has been developed and demonstrated. This procedure involves the utilization of neural networks as state feedback controllers that learn the time-optimal control actions by means of an iterative minimization of both the final time and the final state error for the known and unknown systems with constrained inputs and/or states. The nature of neural networks as a parallel processor would circumvent the problem of "curse of dimensionality". The control law has been demonstrated for a velocity input type motor identified by a genetic algorithm called GENOCOP.