• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.399-406
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• 2009

In this study, Polynomial Radial Basis Function Neural Network(pRBFNN) based on Fuzzy Inference System is designed and its parameters such as learning rate, momentum coefficient, and distributed weight (width of RBF) are optimized by means of Particle Swarm Optimization. The proposed model can be expressed as three functional module that consists of condition part, conclusion part, and inference part in the viewpoint of fuzzy rule formed in 'If-then'. In the condition part of pRBFNN as a fuzzy rule, input space is partitioned by defining kernel functions (RBFs). Here, the structure of kernel functions, namely, RBF is generated from HCM clustering algorithm. We use Gaussian type and Inverse multiquadratic type as a RBF. Besides these types of RBF, Conic RBF is also proposed and used as a kernel function. Also, in order to reflect the characteristic of dataset when partitioning input space, we consider the width of RBF defined by standard deviation of dataset. In the conclusion part, the connection weights of pRBFNN are represented as a polynomial which is the extended structure of the general RBF neural network with constant as a connection weights. Finally, the output of model is decided by the fuzzy inference of the inference part of pRBFNN. In order to evaluate the proposed model, nonlinear function with 2 inputs, waster water dataset and gas furnace time series dataset are used and the results of pRBFNN are compared with some previous models. Approximation as well as generalization abilities are discussed with these results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.3
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• pp.41-48
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• 2004

Finite field multiplication and division are important arithmetic operation in error-correcting codes and cryptosystems. The elements of the finite field GF($2^m$) are represented by bases with a primitive polynomial of degree m over GF(2). We can be easily realized for multiplication or computing multiplicative inverse in GF($2^m$) based on a normal basis representation. The number of product terms of logic function determines a complexity of the Messay-Omura multiplier. A normal basis exists for every finite field. It is not easy to find the optimal normal element for a given primitive polynomial. In this paper, the generating method of normal basis is investigated. The normal bases whose product terms are less than other bases for multiplication in GF($2^m$) are found. For each primitive polynomial, a list of normal elements and number of product terms are presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.403-413
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• 2009

We compare three predistortion methods to prevent signal distortion and spectral re-growth due to the high PAPR (peak-to-average ratio) of OFDM signal and the non-linearity of high-power amplifiers. The three predistortion methods are pth order inverse, indirect learning architecture and look up table. The pth order inverse and indirect learning architecture methods requires less memory and has a fast convergence because these methods use a polynomial model that has a small number of coefficients. Nevertheless the convergence is fast due to the small number of coefficients and the simple computation that excludes manipulation of complex numbers by separate compensation for the magnitude and phase. The look up table method is easy to implement due to simple computation but has the disadvantage that large memory is required. Computer simulation result reveals that indirect learning architecture shows the best performance though the gain is less than 1 dB at $BER\;=\;10^{-4}$ for 64-QAM. The three predistorters are adaptive to the amplifier aging and environmental changes, and can be selected to the requirements for implementation.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.259-259
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• 2003

Genetic algorithms using a Process of genetic evolution of an organism are appropriate for hard problems that have not been solved by any deterministic method. Up to now, the controller design method has been made with the frequency dependent specification but the design method with the time specification has gotten little progress. In this paper, we study the controller design to satisfy the performance of a plant using the generalized Manabe standard form. When dealing with a controller design in the case of two parameter configurations, there are some situations that neither a known pseudo inverse technique nor the inverse method can be applicable. In this case, we propose two methods of designing a controller by the gradient algorithm and the new pseudo inverse method so that the desired closed polynomials are either equalized to or approximated to the designed polynomial. Design methods of the proposed controller are implemented in Java.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.12
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• pp.1845-1855
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• 2004

This paper presents the forward kinematics of the Casing Oscillator that is a construction machine. The Structure of the Casing Oscillator is similar to those of 4 degree-of-freedom mechanisms with a redundancy. With analytical (geometrical) methods, the solutions of the forward position kinematics problem are significantly found by both solving an 8$^{th}$ -order polynomial equation in one unknown variable and using one over-constraint geometrical equation which can be derived under the condition of a redundancy. The proposed forward kinematics has closed-form solutions and allows Auto-Balancing control of the moving platform in real time. Numerical examples are presented and the results are verified by an inverse kinematics analysis.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.54-59
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• 2005

The cylindrical object are widely used as mechanical parts in the manufacturing process. In order to handling those objects using a robot or an automated machine automatically, the pose of the object must be known. The pose can be described by two rotation angles; one angle about the x axis and the other about the y axis. In the many previous researches these angles were obtained by the computationally intensive algorithm, that is, fitting the data as a polynomial and doing pseudo inverse. So that, this method required high performance microprocessor. In this paper in order to avoid complex computation, a new method based on a genetic algorithm is proposed and analyzed through a series of simulations. This algorithm utilized the geometry of the cylindrical shape. The simulation results show that this method find the pose angles very well In most cases, but the computation time is randomly changed because the genetic algorithm is basically one of the random search method.

• Bulletin of the Korean Mathematical Society
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• v.54 no.2
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• pp.507-519
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• 2017

We present an upper bound on the Cheeger constant of a distance-regular graph. Recently, the authors found an upper bound on the Cheeger constant of distance-regular graph under a certain restriction in their previous work. Our new bound in the current paper is much better than the previous bound, and it is a general bound with no restriction. We point out that our bound is explicitly computable by using the valencies and the intersection matrix of a distance-regular graph. As a major tool, we use the discrete Green's function, which is defined as the inverse of ${\beta}$-Laplacian for some positive real number ${\beta}$. We present some examples of distance-regular graphs, where we compute our upper bound on their Cheeger constants.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.12
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• pp.603-610
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• 2002

In this paper, a new economic dispatch algorithm for unit commitment is proposed to improve both the accuracy of the final solution and the calculation speed of economic dispatch. By using the inverse incremental cost functions, economic dispatch can be transformed into a simple optimization problem associated with an n-th order polynomial equation. The proposed method remarkably reduces the computation time with adaptability to any higher order generation cost functions. The proposed method is tested with sample system, which shows that the proposed algorithm yields more accurate and economical generation scheduling results with high computation speed.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.4
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• pp.365-368
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• 1995

Lactation curves of dairy cows were generated using three models, namely; incomplete gamma function (model 1), polynomial inverse function (model 2) and non-linear regression (model 3). Secondary milk yield data of 27 cows which had completed 6 lactations were used in this study. Milk yield records (once a week) throughout the lactation and from the first three months of lactation were fitted to the models. Estimation of total milk yield by model 3 using the data once a week throughout the lactation resulted in smaller % bias and standard error than those generated from model 1 and 2. But, model 2 was more accurate in predicting the 305-day milk yield equivalent closer to actual yields with smaller bias % and error using partial records up to 3 months. Also, model 2 was able to estimate the time to reach peak yield close to the actual data using partial records and model 2 could be used as a tool to advise farmers on appropriate feeding and management practices to be adopted.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1944-1946
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• 2008

This paper analyzed orientation simulation of Stewart platform which is a parallel manipulator of 6-DOF. When platform shape had been given, inverse kinematics as the problem about length of actuator could get an answer using a vector function simply, and forward kinematics as the problem solving shape of platform through the length of actuator could get answer using repetitive and manual explaining Newton-Raphson method because it is expressed a high nonlinear polynomial expression. In addition, for control the Stewart platform it could drive simply and it could confirm the state of orientation in real-time.