• Journal of Power Electronics
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• v.9 no.2
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• pp.188-197
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• 2009

This paper presents an adaptive flux observer to estimate stator flux linkage and stator inductances of an interior permanent-magnet synchronous machine considering magnetic saturation. The concept of static and dynamic inductances due to saturation is introduced in the machine model to describe the relationship between current and flux linkage and the relationship between their time derivatives. A flux observer designed in the stationary reference frame with constant inductance is analyzed in the rotor reference frame by a frequency-response characteristic. An adaptive algorithm for an on-line inductance estimation is proposed and a Lyapunov-based analysis is given to discuss its stability. The dynamic inductances are estimated by using Taylor approximation based on the static inductances estimated by the adaptive method. The simulation and experimental results show the feasibility and performance of the proposed technique.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.50 no.3
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• pp.115-119
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• 2001

This paper presents an efficient and simple method for analyzine maximum simultaneous switching noise (SSN) on ground interconnection networks in CMOS systems. For the derivation of maximum SSN expression, we use ${\alpha}$-power law MOS model and Taylor's series approximation. The accuracy of the proposed method is verified by comparing the results with those of previous researches and HSPICE simulations under the contemporary process parameters and environmental conditions. The proposed method predicts the maximum SSN values more accurately when compared to existing approaches even in most practical cases such that exist some output drivers not in transition.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.241-243
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• 1998

This paper describes a new method for the faster shape optimization of the electromagnetic devices. In a conventional iterative method of shape design optimization using design sensitivity based on a finite element method, meshes for a new shape of the model are generated and a discretized system equation is solved using the meshes in each iteration. They cause much design time. To save this time, a polynomial approximation of the finite element solution with respect to the geometric design parameters using Taylor expansion is constructed. This approximate state variable expressed explicitly in terms of design parameters is employed in a gradient-based optimization method. The proposed method is applied to the shape design of quadrupole magnet.

• Journal of IKEEE
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• v.14 no.2
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• pp.64-68
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• 2010

This paper proposes efficient log and exponent calculation methods using a dual phase instruction set without additional ALU unit for a mobile enviroment. Using the Dual Phase Instruction set, it extracts exponent and mantissa from expression of floating point and calculates 24bit single precision floating point of log approximation using the Taylor series expansion algorithm. And with dual phase instruction set, it reduces instruction excution cycles. The proposed Dual Phase architecture reduces the performance degradation and maintain smaller size.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1223-1232
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• 2011

Tong and Wang's estimator (2005) is a new approach to estimate the error variance using least squares method such that a simple linear regression is asymptotically derived from Rice's lag- estimator (1984). Their estimator highly depends on the setting of a regressor and weights in small sample sizes. In this article, we propose a new approach via a local quadratic approximation to set regressors in a small sample case. We estimate the error variance as the intercept using a ridge regression because the regressors have the problem of multicollinearity. From the small simulation study, the performance of our approach with some existing methods is better in small sample cases and comparable in large cases. More research is required on unequally spaced points.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.255-268
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• 2020

A mixture of multivariate canonical fundamental skew t-distribution (CFUST) has been of interest in various fields. In particular, interest in the unsupervised learning society is noteworthy. However, fitting the model via EM algorithm suffers from significant processing time. The main cause is due to the calculation of many multivariate t-cdfs (cumulative distribution functions) in E-step. In this article, we provide an approximate, but fast calculation method for the in univariate fashion, which is the product of successively conditional univariate t-cdfs with Taylor's first order approximation. By replacing all multivariate t-cdfs in E-step with the proposed approximate versions, we obtain the admissible results of fitting the model, where it gives 85% reduction time for the 5 dimensional skewness case of the Australian Institution Sport data set. For this approach, discussions about rough properties, advantages and limits are also presented.

• The Pure and Applied Mathematics
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• v.12 no.4 s.30
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• pp.275-287
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• 2005

Geometric invariants are basic tools for geometric processing and computer vision. In this paper, we give a linear approximation for the differentiation of the binormal vector field of a space curve by using the forward and backward differences of discrete binormal vectors. Two kind of discrete torsion, say, back-ward torsion $T_b$ and forward torsion $T_f$ can be defined by the dot product of the (backward and forward) discrete differentiation of binormal vectors that are linear approximations of torsion. Using Frenet formula and Taylor series expansion, we give error estimations for the discrete torsions. We also give numerical tests for a curve. Notably the average of $T_b$ and $T_f$ looks more stable in errors.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.623-641
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• 2021

In this paper, numerical treatment of singularly perturbed parabolic delay differential equations is considered. The considered problem have small delay on the spatial variable of the reaction term. To treat the delay term, Taylor series approximation is applied. The resulting singularly perturbed parabolic PDEs is solved using Crank Nicolson method in temporal direction with non-standard finite difference method in spatial direction. A detail stability and convergence analysis of the scheme is given. We proved the uniform convergence of the scheme with order of convergence O(N^-1 + (∆t)²), where N is the number of mesh points in spatial discretization and ∆t is mesh length in temporal discretization. Two test examples are used to validate the theoretical results of the scheme.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.3
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• pp.138-155
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• 2022

To solve the initial value problem we present a new single-step implicit method based on the Euler method. We prove that the proposed method has convergence order 2. In practice, numerical results of the proposed method for some selected examples show an error tendency similar to the second-order Taylor method. It can also be found that this method is useful for stiff initial value problems, even when a small number of nodes are used. In addition, we extend the proposed method by using weighted averages with a parameter and show that its convergence order becomes 2 for the parameter near $\frac{1}{2}$. Moreover, it can be seen that the extended method with properly selected values of the parameter improves the approximation error more significantly.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.397-408
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• 2018

Various methods for accurate parameter estimation have been developed in a sample survey and it is also common to use a ratio estimator or the regression estimator using auxiliary information. The ratio-type estimator has been used in many recent studies and is known to improve the accuracy of estimation by adjusting the ratio estimator. However, various studies are under way to solve it since the ratio-type estimator is biased. In this study, we propose a generalized ratio-type estimator with a new parameter added to the ratio-type estimator to remove the bias. We suggested a method to apply this result to the parameter estimation under the error assumption of heteroscedasticity. Through simulation, we confirmed that the suggested generalized ratio-type estimator gives good results compared to conventional ratio-type estimators.