• 산업기술연구
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• 제10권
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• pp.69-72
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• 1990

In this paper the numerical method for the study of wave reflection from and transmission through submerged permeable breakwaters using the boundary element method is developed. The numerical analysis technique is based on the wave pressure function instead of velocity potential because it is difficult to define the velocity potential in the each region arising the energy dissipation. Also, the non-linear energy dissipation within the submerged porous structure is simulated by introducing the linear dissipation coefficient and the tag mass coefficient equivalent to the non-linear energy dissipation. For the validity of this analysis technique, the numerical results obtained by the present boundary element method are compared with those obtained by the other computation method. Good agreements are obtained and so the validity of the present numerical analysis technique is proved.

• 소음진동
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• 제9권3호
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• pp.472-476
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• 1999

The effect of static preload on the dynamic properties of rubber materials is rather important, especially when good isolation characteristics are required at high frequencies. However, there are still few papers for dynamic characteristics of compressed rubber components. It was demonstrated in reference (4) that for bonded rubber material of a cylindrical shape, a simplified theory equation between linear dynamic and nonlinear static behavior of rubber material was useful to predict their combined effects. This paper presents the second part of the study. It is confirmed that for the compressed rubber material, the stress can be factored into a function of frequency and a function of strain(stretch). The finite element methodis applied to analyze non-linear large deformation of rubber material and its results are compared with those of a simplified theory equation. The predicted dynamic material properties based on non-linear static finite element analyses have a good agreement of experimental results and those based on simplified theory equation.

• ETRI Journal
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• 제15권2호
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• pp.35-51
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• 1993

This paper presents function approximation based on nonparametric estimation. As an estimation model of function approximation, a three layered network composed of input, hidden and output layers is considered. The input and output layers have linear activation units while the hidden layer has nonlinear activation units or kernel functions which have the characteristics of bounds and locality. Using this type of network, a many-to-one function is synthesized over the domain of the input space by a number of kernel functions. In this network, we have to estimate the necessary number of kernel functions as well as the parameters associated with kernel functions. For this purpose, a new method of parameter estimation in which linear learning rule is applied between hidden and output layers while nonlinear (piecewise-linear) learning rule is applied between input and hidden layers, is considered. The linear learning rule updates the output weights between hidden and output layers based on the Linear Minimization of Mean Square Error (LMMSE) sense in the space of kernel functions while the nonlinear learning rule updates the parameters of kernel functions based on the gradient of the actual output of network with respect to the parameters (especially, the shape) of kernel functions. This approach of parameter adaptation provides near optimal values of the parameters associated with kernel functions in the sense of minimizing mean square error. As a result, the suggested nonparametric estimation provides an efficient way of function approximation from the view point of the number of kernel functions as well as learning speed.

• Journal of applied mathematics & informatics
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• 제22권1_2호
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• pp.317-329
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• 2006

In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.204-208
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• 2001

In this paper, we induce the linear transfer function of Downcomer water level of NPP(Nuclear Power Plant) Steam Generator using Genetic Algorithm and Levenberg-Marquardt Algorithm. The characteristic of NPP S/G mechanism is so high-non-linear that it is hard to achieve mathematical expression. So we use non-mathematical Algorithms to get the model function of NPP S/G water level. S/G level controller would be designed with this transfer function as the plant.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.182-186
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• 2004

This paper describes an advanced compensation for non-linear functions designed to remove steering aberrations from phased array antennas. This system alters the steering command applied to the antenna in a way that the appropriate angle commands are given to the array steering software for the antenna to point to the desired position instead of squinting. Artificial neural networks are used to develop the inverse function necessary to correct the aberration. Also a straightforward antenna steering function is implemented with neural networks for the 9-term polynomials of forward steering function. In all cases the aberration is removed resulting in small RMS angular errors across the operational angle space when the actual antenna position is compared with the desired position. The use of neural network model provides a method of producing a non-linear system that can correct antenna performance and demonstrates the feasibility of generating an inverse steering algorithm.

• 전기학회논문지
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• 제57권3호
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• pp.458-465
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• 2008

In this paper, we propose a non-fragile guaranteed cost controller design method for uncertain linear systems with constant delyas in state. The norm bounded and time-varying uncertainties are subjected to system and controller design matrices. A quadratic cost function is considered as the performance measure for the system. Based on the Lyapunov method, an LMI(Linear Matrix Inequality) optimization problem is established to design the controller which uses information of delayed state and minimizes the upper bound of the quadratic cost function for all admissible system uncertainties and controller gain variations. Numerical examples show the effectiveness of the proposed method.

• 한국철도학회논문집
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• 제5권1호
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• pp.40-47
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• 2002

In this study, and analytical method for ride sensitivity analysis of a train with non-linear suspension elements are proposed. Non-linear characteristics of springs and dampers for primary and secondary suspensions of a train are parameterized using polynomial interpolation. Vertical dynamic model of a three-body train running on straight rail with the predetermined roughness expressed in terms of spectral density function is set up and its equations of motion for ride analysis are derived. Using the direct differentiation method, sensitivity equations of the vertical dynamic model with respect to design parameters associated with non-linearity of suspensions are obtained. Based on the sensitivity analysis, improvement of ride is achieved by varying appropriate suspension parameters.

• Journal of applied mathematics & informatics
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• 제9권1호
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• pp.61-76
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• 2002

The robust non-fragile guaranteed cost control problem is studied in this paper for class of uncertain linear large-scale systems with time-varying delays in subsystem interconnections and given quadratic cost functions. The uncertainty in the system is assumed to be norm-hounded arid time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound far all admissible uncertainties. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost contrellers is 7iven in terms of the feasible solution to a certain LMI. Finally, in order to show the application of the proposed method, a numerical example is included.

• 산업경영시스템학회지
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• 제34권2호
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• pp.60-67
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• 2011

Since the non-metric Multidimensional scaling (nMDS), a data visualization technique, provides with insights about engineering, economic, and scientific applications, it is widely used for analyzing large non-metric multidimensional data sets. The nMDS requires a fitness function to measure fit of the proximity data by the distances among n objects. Most commonly used fitness functions are nonlinear and have a difficulty to find a good configuration. In this paper, we propose a new fitness function, an absolute value type, and show its advantages.