• KSCE Journal of Civil and Environmental Engineering Research
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• v.2 no.2
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• pp.29-38
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• 1982

Nonlinear hydrological model containing the nonlinearity of effective rainfall, lag time and runoff is presented. In the evaluation of rainfall excess, the polynomial fitting method for total rainfall, 5 day antecedant rainfall and direct runoff is developed. In the application to actual watershed, the estimated model parameters of nonlinear lag model reflecting the nonlinearity of lag time are compared with the parameters, by both the fitting method and the correlation, model which are the modified version of the storage function model. The Successive Approximation Method in mathematical solution and Newton-Rhapson method in numerical solution are found to be superior to the conventional numerical graphic method in the analysis of nonlinear processes.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.1
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• pp.17-27
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• 2011

A selection experiment for reduced residual feed intake (RFI) in Yorkshire pigs consisted of a line selected for lower RFI (LRFI) and a random control line (CTRL). Longitudinal measurements of daily feed intake (DFI) and body weight (BW) from generation 5 of this experiment were used. The objectives of this study were to evaluate the use of random regression (RR) and nonlinear mixed models to predict DFI and BW for individual pigs, accounting for the substantial missing information that characterizes these data, and to evaluate the effect of selection for RFI on BW and DFI curves. Forty RR models with different-order polynomials of age as fixed and random effects, and with homogeneous or heterogeneous residual variance by month of age, were fitted for both DFI and BW. Based on predicted residual sum of squares (PRESS) and residual diagnostics, the quadratic polynomial RR model was identified to be best, but with heterogeneous residual variance for DFI and homogeneous residual variance for BW. Compared to the simple quadratic and linear regression models for individual pigs, these RR models decreased PRESS by 1% and 2% for DFI and by 42% and 36% for BW on boars and gilts, respectively. Given the same number of random effects as the polynomial RR models, i.e., two for BW and one for DFI, the non-linear Gompertz model predicted better than the polynomial RR models but not as good as higher order polynomial RR models. After five generations of selection for reduced RFI, the LRFI line had a lower population curve for DFI and BW than the CTRL line, especially towards the end of the growth period.

• Aerospace Engineering and Technology
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• v.8 no.2
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• pp.75-82
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• 2009

In order to help general users to analyze the KOMPSAT-2 data, an application of sensor modeling to commercial software was explained in this document. The sensor modeling is a basic step to extract the quantity and quality information from KOMPSAT-2 data. First, we introduced the contents and type of ancillary data offered with KOMPSAT-2 PAN image data, and explained how to use it with commercial software. And then, we applied the polynomial-base and refine RFM sensor modeling with ground control points. In the polynomial-base sensor modeling, the accuracy which is average RMSE of check points is highest when the satellite position was calculated by type of 1st order function and the satellite attitude was calculated by type of 1st order function for (Y axis), (Z axis) or constant for (X axis), (Y axis), (Z axis) in perspective center position and satellite attitude parameters. As a result of refine RFM sensor modeling, the accuracy is less than 1 pixel when we applied affine model..

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2352-2360
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• 2011

In this paper, we introduce a comprehensive design methodology of Radial Basis Function Neural Networks (RBFNN) that is based on mechanism of clustering and optimization algorithm. We can divide some clusters based on similarity of input dataset by using clustering algorithm. As a result, the number of clusters is equal to the number of nodes in the hidden layer. Moreover, the centers of each cluster are used into the centers of each receptive field in the hidden layer. In this study, we have applied Fuzzy-C Means(FCM) and K-Means(KM) clustering algorithm, respectively and compared between them. The weight connections of model are expanded into the type of polynomial functions such as linear and quadratic. In this reason, the output of model consists of relation between input and output. In order to get the optimal structure and better performance, Particle Swarm Optimization(PSO) is used. We can obtain optimized parameters such as both the number of clusters and the polynomial order of weights connection through structural optimization as well as the widths of receptive fields through parametric optimization. To evaluate the performance of proposed model, NXT equipment offered by National Instrument(NI) is exploited. The situation awareness system-related intelligent model was built up by the experimental dataset of distance information measured between object and diverse sensor such as sound sensor, light sensor, and ultrasonic sensor of NXT equipment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.191-199
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• 2006

In this paper, we propose a method to implement a predistorter of the $rho$-th order inverse filter structure to prevent signal distortion and spectral re-growth due to the high PAPR (peak-to-average ratio) of the OFDM signals and the non-linearity of high-power amplifiers. We model the memory-less non-linearity of the high-power amplifier with a polynomial model and utilize the inverse of the model, the $rho$-th order inverse filter, for the predistorter. Once the non-linearity is modeled with a polynomial, since we can determine the $rho$-th order inverse filter only with the coefficients of the polynomial, large memory is not required. To update the coefficients of the non-linear high-power amplifier model, we can use LMS or RLS algorithms. The convergence speed is high since the number of coefficients is small, and the computation is simple since manipulation of complex numbers is not necessary.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.130-140
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• 1998

This paper presents a method to estimate subpixel accuracy motion vectors using a mathermatical model withoug interpolation. the proposed method decides the coefficients of mathematical model, which represents the motion vector which is achieved by full search. And then the proposed method estimates subpixel accuracy motion vector from achieved mathematical model. Step by step mathematical models such as type 1, type 2, type 3, modified bype 2, modified type 3, and Partial Interpolation type 3 are presented. In type 1, quadratic polynomial, which has 9 unknown coefficients and models the 3by 3 pixel plane, is used to get the subpixel accuracy motion vectors by inverse matrix solution. In type 2 and 3, each quadratic polynomial which is simplified from type 1 has 5 and 6 unknown coefficients and is used by least square solution. Modified type 2 and modified type 3 are enhanced models by weighting only 5 pixels out of 9. P.I. type 3 is more accurate method by partial interpolation around subpixel which isachieved by type 3. LThese simulation results show that the more delicate model has the better performance and modified models which are simplified have excellent performance with reduced computational complexity.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.16-21
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• 2004

This paper presents an approximation method for simplifying a high-order transfer function to a low-order transfer function. A model reduction is based on minimizing the error function weighted by the numerator polynomial of reduced systems. The proposed methods provide better low frequency fit and a computer aided algorithm that estimates the coefficients vector for the numerator and denominator polynomial on the simplified systems from an overdetermined linear system constructed by frequency responses of the original systems. Two examples are given to illustrate the feasibilities of the suggested schemes.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.619-627
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• 2002

It is unpractical for the optimal design theory based on the given model and assumption to be applied to the real-world experimentation. Particularly, when the experimenter feels it necessary to consider multiple objectives in experimentation, its modified version of optimality criteria is indeed desired. The constrained optimal design is one of many methods developed in this context. But when the number of constraints exceeds two, there always exists a problem in specifying the lower limit for the efficiencies of the constraints because the “infeasible solution” issue arises very quickly. In this paper, we developed a sequential approach to tackle this problem assuming that all the constraints can be ranked in terms of importance. This approach has been applied to the polynomial regression model.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.129-132
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• 2001

This paper presents an efficient method to estimate the maximum SSN (simultaneous switching noise) for ground interconnection networks in CMOS systems using Taylor's series and analyzes the truncation error that has occurred in Taylor's series approximation. We assume that the curve form of noise voltage on ground interconnection networks is linear and derive a polynomial expression to estimate the maximum value of SSN using $\alpha$-power MOS model. The maximum relative error due to the truncation is shown to be under 1.87% through simulations when we approximate the noise expression in the 3rd-order polynomial.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.519-536
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• 1995

In the design of experiments for response surface analysis, sometimes it is of interest to estimate the difference of responses at two points. If differences at points close together are involved, the design that reliably estimates the slope of response surface is important. This idea was conceptualized by slope rotatability by Hader & Park (1978) and Park (1987). Until now, second order polynomial models were only studied for slope ratatability. In this paper, we will propose the necessary and sufficient conditions for slope rotatability over all directions for the thired order polynomial models in two, three and four independent variables. Also practical slope rotatable designs over all directions for two independent variables are suggested.