• 한국통신학회논문지
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• 제19권12호
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• pp.2479-2488
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• 1994

본 논문에서는 음원신호의 새로운 동적 모델링 기법을 제안하였다. 제안된 동적 모델링 기법을 적용하여, 평균 3.8Kbps와 4.4 Kbps에서 작동하는 두개의 가변 저 전송을 호모몰픽 보코더를 구현하였다. 본 논문에서 제시한 모델링 기법의 성능은 청음 테스트를 사용하여 분석하였으며, 청음 테스트에서는 본 논문에서 구현한 두개의 코더가 기존의 정적 음원 모델링 방법을 사용하여 Chung과 Schafer에 의하여 구현된 4.8Kbps 호모몰픽 보코더가 비교되었다. 제안된 동적 음원 모델링 기법이 음성통신의 평균 전송율을 낮추면서, 반면에 합성된 음의 음질을 향상시킴을, 청음 테스트를 통하여 보였다.

• Journal of Computing Science and Engineering
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• 제6권3호
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• pp.219-226
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• 2012

Recently, shape analysis of human organs has achieved much attention, owing to its potential to localize structural abnormalities. For a group-wise shape analysis, it is important to accurately restore the shape of a target structure in each subject and to build the inter-subject shape correspondences. To accomplish this, we propose a shape modeling method based on the Laplacian deformation framework. We deform a template model of a target structure in the segmented images while restoring subject-specific shape features by using Laplacian surface representation. In order to build the inter-subject shape correspondences, we implemented the progressive weighting scheme for adaptively controlling the rigidity parameter of the deformable model. This weighting scheme helps to preserve the relative distance between each point in the template model as much as possible during model deformation. This area-preserving deformation allows each point of the template model to be located at an anatomically consistent position in the target structure. Another advantage of our method is its application to human organs of non-spherical topology. We present the experiments for evaluating the robustness of shape modeling against large variations in shape and size with the synthetic sets of the second cervical vertebrae (C2), which has a complex shape with holes.

• 한국전자파학회논문지
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• 제21권11호
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• pp.1220-1228
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• 2010

본 논문에서는 비선형 RF 전력 증폭기의 효율적인 다항식 기반의 이산 신호 모델링 방법을 제시하였다. 비선형 RF 증폭기의 입, 출력 신호의 샘플링 과정을 통하여 이산 비선형 모델을 추출하는 과정을 기술하고, 테일러 급수와 메모리 다항식 구조를 이용한 다항식 기반의 비선형 이산 모델에서 모델 인자인 샘플률, 비선형 차수, 최대 메모리 깊이의 변화에 따른 모델의 오차를 분석하였다. 다항식 기반의 비선형 모델에서 오차는 샘플률, 비선형 차수, 최대 메모리 깊이에 대하여 특정 값 이후부터 일반적으로 수렴하는 특성을 보인다. 이에 모델 인자값에 따른 시스템의 복잡성을 고려하는 효율적인 이산 신호 모델링 기법을 제시하였다. 모델링 효율 지수를 정의하고, 이를 활용하여 최적의 모델 인자 값을 추출하는 방법을 제시하였다. 제시한 방법을 WiBro, WCDMA 등의 다양한 신호를 가지는 RF 전력 증폭기의 모델링에 적용하고, 제시한 방법의 효율성을 검증하였다. 제안된 기법은 빠른 속도의 모델링과 저렴한 가격의 디지털부를 사용할 수 있게 하여 차후 광대역 송신기에서의 빠른 속도와 낮은 가격의 디지털 전치 왜곡기 구성 등에 활용될 수 있을 것으로 사료된다.

• 한국CDE학회논문집
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• 제19권1호
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• pp.41-49
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• 2014

For the reuse of the existing 3D block model of a ship, we analyze the hull modeling process using AVEVA Marine which is a representative CAD (Computer-Aided Design) system for the shipbuilding. In the AVEVA Marine environment where the design engineer makes 3D model on the 2D view that is so-called 2.5D, it cannot be possible to copy to reuse the block model just simply copying the 3D feature model itself like in the general mechanical CAD system or Smart Marine 3D which are on the basis of the 3D model representation. In this paper, we analyze the scheme file where the 3D model is defined in AVEVA Marine so that we develop the program for the block copy and the translation using this scheme file. It is significant that this program can be immediately available as a real-world application on the AVEVA Marine environment.

• 한국지능시스템학회논문지
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• 제12권6호
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• pp.577-582
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• 2002

Neural network can be trained to approximate an arbitrary nonlinear function of multivariate data like the mini-mill crown values in Automatic Shape Control. The trained weights of neural network can evaluate or generalize the process data outside the training vectors. Sometimes, the blind modeling of the process data is necessary to compare with the scattered analytical model of mini-mill process in isolated electro-mechanical forms. To come up with a viable model, we propose the blind neural-based range-division domain-clustering piecewise-linear modeling scheme. The basic ideas are: 1) dividing the range of target data, 2) clustering the corresponding input space vectors, 3)training the neural network with clustered prototypes to smooth out the convergence and 4) solving the resulting matrix equations with a pseudo-inverse to alleviate the ill-conditioning problem. The simulation results support the effectiveness of the proposed scheme and it opens a new way to the data analysis technique. By the comparison with the statistical regression, it is evident that the proposed scheme obtains better modeling error uniformity and reduces the magnitudes of errors considerably. Approximatly 10-fold better performance results.

• 한국시뮬레이션학회논문지
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• 제11권1호
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• pp.71-82
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• 2002

One of the most important things in the research for MIN-based switch operation the management scheme of network cycle. In the traditional MIN, when the receving buffer module is empty, the sell has to move forward the front-most buffer position by the characteristic of the conventional FIFO queue. However, most of buffer modules are almost always full for practical amount of input loads. The long network cycle of the traditional scheme is thus a substantial waste of bandwidth. In this paper, we propose the modeling method for the input and multi-buffered MIN with unit step buffering scheme, In spite of simplicity, simulation results show that the proposed model is very accurate comparing to previous modeling approaches in terms of throughput and the trend of delay.

• 한국환경과학회지
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• 제19권2호
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• pp.137-148
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• 2010

This paper investigates the characteristics of turbulence schemes. Turbulence closures are fundamental for modeling the atmospheric diffusion, transport and dispersion in the boundary layer. In particular, in non-homogeneous conditions, a proper description of turbulent transport in planetary boundary layer is fundamental aspect. This study is based on the Regional Atmospheric Modeling System (RAMS) and combines four different turbulence schemes to assess if the different schemes have a impact on simulation results of vertical profiles. Two of these schemes are Isotropc Deformation scheme (I.Def) and Anisotropic deformation scheme (A.Def) that are simple local scheme based on Smagorinsky scheme. The other two are Mellor-Yamada scheme (MY2.5) and Deardorff TKE scheme (D.TKE) that are more complex non-local schemes that include a prognostic equation for turbulence kinetic energy. The simulated potential temperature, wind speed and mixing ratio are compared against radiosonde observations from the study region. MY2.5 shows consistently reasonable vertical profile and closet to observation. D.TKE shows good results under relatively strong synoptic condition especially, mixing ratio simulation. Validation results show that all schemes consistently underestimated wind speed and mixing ratio but, potential temperature was somewhat overestimated.

• 한국CDE학회논문집
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• 제11권4호
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• pp.235-245
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• 2006

This paper proposes a CSG-based representation scheme for heterogeneous objects including multi-material objects and Functionally Graded Materials (FGMs). In particular, this scheme focuses on the construction of complicated heterogeneous objects guaranteeing desired material continuities at all the interfaces. In order to create various types of heterogeneous primitives, we first describe methods for specifying material composition functions such as geometry-independent, geometry-dependent functions. Constructive Material Composition (CMC) and corresponding heterogeneous Boolean Operators (e.g. material union, difference, intersection. and partition) are then proposed to illustrate how material continuities are dealt with. Finally, we describe the model hierarchy and data structure for computer representation. Even though the proposed scheme alone is sufficient for modeling all sorts of heterogeneous objects, the proposed scheme adopts a hybrid representation between CSG and decomposition. That is because hybrid representation can avoid the unnecessary growth of binary trees.

• Structural Engineering and Mechanics
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• 제16권6호
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• pp.643-654
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• 2003

Two real-time modeling prediction (RMP) schemes are presented in this paper for analyzing the behavior of deep excavations during construction. The first RMP scheme is developed from the traditional AR(p) model. The second is based on the simplified Elman-style recurrent neural networks. An on-line learning algorithm is introduced to describe the dynamic behavior of deep excavations. As a case study, in-situ measurements of an excavation were recorded and the measured data were used to verify the reliability of the two schemes. They proved to be both effective and convenient for predicting the behavior of deep excavations during construction. It is shown through the case study that the RMP scheme based on the neural network is more accurate than that based on the traditional AR(p) model.

• 대한전기학회논문지
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• 제43권5호
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.