• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.124-129
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• 2021

In this paper, an optimal controller design that guarantees absolute stability is proposed. The order of application of the thesis determines whether the delay time is included, and if the delay time is included, the delay time is approximated through the Pade approximation method. Then, the open loop transfer function for the process model and the controller transfer function is obtained, and the absolute stability interval is calculated by the Routh-Hurwitz discrimination method. In the last step, the optimal Proportional and Integral and Derivative(PID) control parameter value is calculated using a genetic algorithm using the interval obtained in the previous step. As a result, it was confirmed that the proposed method guarantees stability and is superior to the existing method in performance index by designing an optimal controller. If we study the compensation method for the delay time in the future, it is judged that better performance indicators will be obtained.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.505-514
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• 2020

Since a large amount of training data is typically needed to train Deep Neural Networks (DNNs), a parallel training approach is required to train the DNNs. The Stochastic Gradient Descent (SGD) algorithm is one of the most widely used methods to train the DNNs. However, since the SGD is an inherently sequential process, it requires some sort of approximation schemes to parallelize the SGD algorithm. In this paper, we review various efforts on parallelizing the SGD algorithm, and analyze the computational overhead, communication overhead, and the effects of the approximations.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.63-70
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• 1999

This paper is proposed a new method to deal with the optimized auto-tuning for the Pill controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nichols method. So we can find the parameters of Pill controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of Pill controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of Pill controller is found by Neural-Network Program.rogram.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.23-28
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• 2004

In EIT, various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. In this paper, a SPSA approach is proposed for the solution of the EIT image reconstruction. Results of numerical experiments of EIT solved by the SPSA approach are presented and compared to that obtained by the modified Newton-Raphson(mNR) method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11C
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• pp.1111-1118
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• 2007

This paper presents our study of throughput enhancement achieved by selection diversity in a multiuser system, called multiuser diversity (MUDiv), using a new asymptotic approach. The MUDiv gain is evaluated by deriving an asymptotic formula for the throughput enhancement from the MUDiv gain as a simple closed form introducing a Puiseux series. The formula shows that the MUDiv gain is independent of the signal-to-noise ratio (SNR). This concept can be extended to analysis applicable to scheduling algorithms, such as Max C/I and proportional fair scheduling. The MUDiv gain throughput analysis is verified using Monte-Carlo simulations.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2552-2554
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• 2005

제어기 설계에서 이득여유와 위상여유는 견실성 및 안정도 판별의 중요한 척도로 사용되며, 그 중 위상여유는 시스템의 성능지수와 관련된다. 이와 같은 이유로 이득여유와 위상여유의 안정도를 고려한 제어기의 설계방법이 연구되어지고 있다. 근래 Weng Khuen Ho와 Chang Chieh Hang이 제안한 설계방법은 복잡한 계산을 필요로 하는 arctan 함수를 1차 선형함수로 근사화 하여 복잡도를 감소시키면서도 원하는 이득여유와 위상여유를 만족시키는 제어기의 파라미터를 찾았다. 하지만 이 방법은 실제의 arctan 함수를 사용하는 것이 아니라 근사화된 수식을 사용함으로써 오차가 수반되어 원하는 설계조건을 만족 하지 못한다. 따라서 본 논문은 이러한 오차를 최소화하기 위해서 최적화 알고리즘을 이용한 이득여유와 위상여유를 보상하는 PID 제어기를 설계하였다.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.383-392
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• 2010

Modelling financial phenomena with diffusion processes is frequently used technique. This study reviews the earlier researches on the approximation problem of transition densities of diffusion processes, which takes important roles in estimating diffusion processes, and consider the method to obtain the coefficients of series efficiently, in series approximation method of transition densities. We developed a new efficient algorithm to compute the coefficients which are represented by repeated Dynkin operator on Hermite polynomial.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.6 s.237
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• pp.842-851
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• 2005

In this paper, a new method for constrained optimization of noisy functions is proposed. In approximate optimization using response surface methods, if constraints have severe noise, the approximate feasible region defined by approximate constraints is apt to include some of the infeasible region defined by actual constraints. This can cause the approximate optimum to converge into the infeasible region. In the proposed method, the approximate optimization is performed with the approximate constraints shifted by their deviations, which are calculated using a diagonal quadratic response surface method. This can prevent the approximate optimum from converging into the infeasible region. To fit the objective and constraints into diagonal quadratic models, we select the center and 4 additional points along each axis of design variables as experimental points. The deviation of each function is calculated using the differences between the real and approximate function values at the experimental points. A sequential approximate optimization technique based on the trust region algorithm is adopted to manage approximate models. The proposed approach is validated by solving some design problems. The results of the problems show the effectiveness of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1199-1208
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• 2005

Nowadays, it is performed actively to optimize by using an approximate model. This is called the approximate optimization. In addition, the sequential approximate optimization (SAO) is the repetitive method to find an optimum by considering the convergence of an approximate optimum. In some recent studies, it is proposed to increase the fidelity of approximate models by applying the sequential sampling. However, because the accuracy and efficiency of an approximate model is directly connected with the design area and the termination criteria are not clear, sequential sampling method has the disadvantages that could support an unreasonable approximate optimum. In this study, the SAO is executed by using trust region, Kriging model and Optimal Latin Hypercube design (OLHD). Trust region is used to guarantee the convergence and Kriging model and OLHD are suitable for computer experiment. finally, this SAO method is applied to various optimization problems of highly nonlinear mathematical functions. As a result, each approximate optimum is acquired and the accuracy and efficiency of this method is verified by comparing with the result by established method.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.625-627
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• 2001

기존의 종이지도를 수치지도 처리과정으로 얻어진 등고선(contour line) 데이터는 원격탐사(Remote Sensing)와 지리정보시스템(GIS)의 응용분야에서 주로 사용되어지는 데이터이다. 이러한 등고선은 해당 지역의 DTM(Digital Terrain Model) 데이터 생성을 위해 보간(interpolation)하여 생성하는 데 연구가 집중되어 왔다. 본 논문에서는 DEM(Digital levation Model)으로부터 얻어진 등고선 데이터를 이용하여 사용자에게 3차원으로 가시화 해 줄 수 있는 기법을 소개한다. 등고선 추출을 위한 방법으로는 기존의 소개되어진 Marching Square 알고리즘을 적용하였고, 지역적인 최고점(local minimum)과 최소점(maximum)을 구하기 위해 등고선을 열린 등고선(open contour)과 닫힌 등고선(closed contour)으로 분류하게 된다. 지역적 최고, 최소점을 찾기 위한 탐색공간을 줄이기 위해 닫힌 등고선만을 닫힌 등고만을 대상으로 등고선 트리를 생성하였으며, 생성된 트리의 리프노드에 대해서 최고, 최소점에 대한 근사(approximation)를 수행하게 된다. 이렇게 구해진 근사된 장점들과 등고선 데이털 입력으로 하여 제한된 딜로니 삼각분할(Constrained Delaunay Triangulation)을 수행함으로써, 3차원 지형을 재구성할 수 있다. 실험에서 간단한 그리드 샘플데이터와 USGS로 획득한 데이터를 이용하여 속도 측정을 하였다. 결과적으로 저장공간 측면에서 적은 량의 데이터를 가지면서 등고선을 표현할 수 있는 3차원 지형을 랜더링할 수가 있음을 알 수 있다.