• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1177-1180
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• 1993

In this paper, a fuzzy-neural interpolating network is proposed to efficiently approximate a nonlinear function. Specifically, basis functions are first constructed by Fuzzy Membership Function based Neural Networks (FMFNN). And the fuzzy similarity, which is defined as the degree of matching between actual output value and the output of each basis function, is employed to determine initial weighting of the proposed network. Then the weightings are updated in such a way that square of the error is minimized. To show the capability of function approximation of the proposed fuzzy-neural interpolating network, a numerical example is illustrated.

• 제어로봇시스템학회논문지
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• 제9권6호
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• pp.435-441
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• 2003

This paper addresses that an approximation and tracking control of realtime recurrent neural networks(RTRN) using two-dimensional iterative teaming algorithm for an electro-hydraulic servo system. Two dimensional learning rule is driven in the discrete system which consists of nonlinear output fuction and linear input. In order to control the trajectory of position, two RTRN with the same network architecture were used. Simulation results show that two RTRN using 2-D learning algorithm are able to approximate the plant output and desired trajectory to a very high degree of a accuracy respectively and the control algorithm using two identical RTRN was very effective to trajectory tracking of the electro-hydraulic servo system.

• 대한전기학회논문지:전력기술부문A
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• 제52권5호
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• pp.263-270
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• 2003

In field applications, to represent the degree of voltage unbalance, the maximum voltage deviation from the average is preferred to the voltage unbalance factor based on symmetrical component analysis. This paper first clarifies the relationship between the voltage unbalance factor and the maximum deviation factor showing that the maximum deviation factor approximates the voltage unbalance factor under relatively low unbalanced conditions. Several alternative ways of approximation are introduced and examined by comparing with the conventional maximum deviation factor. It appears that these alternatives provide more accurate approximation to the voltage unbalance factor over wider range of voltage unbalance while maintaining simplicity in their formula.

• 한국통신학회논문지
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• 제21권11호
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• pp.2942-2953
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• 1996

This paper studies the effect of intersymbol interference due to sampling-time jitter on the worst-case bit error probability in a digital modultation over an additive white Gaussian noise channel, with the squared-root raised-cosine filters in the transmitter and the receiver. It derives approximation formulas using the Taylor series approximations. the principal results of this paper is the relationship between the worst-casse bit error probability, the degree of jitter, the roll factor of the raised cosine filter, and other quantities. Numerical results show, as expected, that the intersymbol interference decreases as the roll-off factor increases and the jitter decreases. They also show that the approximation formulas are accurate for smally intersymbol interference, i.e., for large roll-noise ratio $E_{b/}$ $N_{0}$.leq.7 dB and begin to lose accuracy for larger signal-to-noise ratio.o.o.

• 유공압시스템학회논문집
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• 제1권1호
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• pp.1-9
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• 2004

This paper addresses an approximation and tracking control of recurrent neural networks(RNN) using two-dimensional iterative learning algorithm for an electro-hydraulic servo system. And two dimensional learning rule is driven in the discrete system which consists of nonlinear output function and linear input. In order to control the trajectory of position, two RNN's with the same network architecture were used. Simulation results show that two RNN's using 2-D learning algorithm are able to approximate the plant output and desired trajectory to a very high degree of a accuracy respectively and the control algorithm using two same RNN was very effective to control trajectory tracking of electro-hydraulic servo system.

• 한국정밀공학회지
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• 제20권6호
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• pp.62-70
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• 2003

This paper deals with a approximation and tracking control of hydraulic servo system using a real time recurrent neural networks (RTRN) with 2-dimensional iterative learning rule. And it was driven that 2-dimensional iterative learning rule in discrete time. In order to control the trajectory of position, two RTRN with same network architecture were used. Simulation results show that two RTRN using 2-D learning algorithm is able to approximate the plant output and desired trajectory to a very high degree of a accuracy respectively and the control algorithm using two same RTRN was very effective to control trajectory tracking of electro-hydraulic servo system.

• Journal of the Optical Society of Korea
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• 제18권6호
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• pp.706-713
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• 2014

An enhanced 360-degree integral-floating three-dimensional display system using a hexagonal lens array and a hidden point removal operator is proposed. Only the visible points of the chosen three-dimensional point cloud model are detected by the hidden point removal operator for each rotating step of the anamorphic optics system, and elemental image arrays are generated for the detected visible points from the corresponding viewpoint. Each elemental image of the elemental image array is generated by a hexagonal grid, due to being captured through a hexagonal lens array. The hidden point removal operator eliminates the overlap problem of points in front and behind, and the hexagonal lens array captures the elemental image arrays with more accurate approximation, so in the end the quality of the displayed image is improved. In an experiment, an anamorphic-optics-system-based 360-degree integral-floating display with improved image quality is demonstrated.

• Journal of information and communication convergence engineering
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• 제9권4호
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• pp.424-427
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• 2011

The paper is devoted to problem of spline approximation. A new method of nodes location for curves and surfaces computer construction by means of B-splines, of Reyabenko's splines and results of simulink-modeling is presented. The advantages of this paper is that we comprise the basic spline with classical polynomials both on accuracy, as well as degree of paralleling calculations are also show's.

• Journal of applied mathematics & informatics
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• 제12권1_2호
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• pp.67-79
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• 2003

An approximation for the bias in lag window estimators of the degree of differencing in fractionally integrated time series models is derived. The expression obtained is compared with the observed bias from simulations for various windows.

• East Asian mathematical journal
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• 제38권3호
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• pp.365-377
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• 2022

In this paper, we present a new class of interpolatory Hermite subdivision schemes of order 2 reproducing polynomials. Each member in this class, denoted by H_n for n ≥ 1, preserves polynomials of degree up to 4n + 1 admitting the approximation order of 4n + 2. Furthermore, it has free parameters which provide flexibility in designing curves/surfaces. H₁, the simplest and the most attractive scheme in this class, achieves C⁴ smoothness with the parameters in certain ranges, and its performance is demonstrated with numerical examples.