• Journal of the Korean Mathematical Society
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• v.35 no.4
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• pp.903-931
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• 1998

Since the modular curves X(N) = $\Gamma$(N)\(equation omitted)＊ (N =1,2,3) have genus 0, we have field isomorphisms K(X(l))(equation omitted)C(J), K(X(2))(equation omitted)(λ) and K(X(3))(equation omitted)( $j_3$) where J, λ are the classical modular functions of level 1 and 2, and $j_3$ can be represented as the quotient of reduced Eisenstein series. When N = 4, we see from the genus formula that the curve X(4) is of genus 0 too. Thus the field K(X(4)) is a rational function field over C. We find such a field generator $j_4$(z) = x(z)/y(z) (x(z) = $\theta$$_3$((equation omitted)), y(z) = $\theta$$_4$((equation omitted)) Jacobi theta functions). We also investigate the structures of the spaces $M_{k}$($\Gamma$(4)), $S_{k}$($\Gamma$(4)), M(equation omitted)((equation omitted)(4)) and S(equation omitted)((equation omitted)(4)) in terms of x(z) and y(z). As its application, we apply the above results to quadratic forms.rms.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.797-802
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• 2005

We generate simplex polynomials by using a method, which produces an OPS in (d + 1) variables from an OPS in d variables and the Jacobi polynomials. Also we obtain a partial differential equation of the form $${\Sigma}_{i,j=1}^{d+1}\;A_ij{\frac{{\partial}^2u}{{\partial}x_i{\partial}x_j}}+{\Sigma}_{i=1}^{d+1}\;B_iu\;=\;{\lambda}u$$, which has simplex polynomials as solutions, where ${\lambda}$ is the eigenvalue parameter.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.287-290
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• 1995

Recently H$_{\infty}$ control theory for nonlinear systems based on the Hamilton-Jacobi inequality has been developed. In this paper, we apply the state feedback controller solved via Riccati equation to a semi-active suspension model, two degree of freedom vehicle model, and show that it is effective for vibration control..

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.440-444
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• 1998

In this paper, we consider numerical solution of a H-J-B (Hamilton-Jacobi-Bellman) equation of elliptic type arising from the stochastic control problem. For the numerical solution of the equation, we take an approach involving contraction mapping and finite difference approximation. We choose the It(equation omitted) type stochastic differential equation as the dynamic system concerned. The numerical method of solution is validated computationally by using the constructed test case. Map of optimal controls is obtained through the numerical solution process of the equation. We also show how the method applies by taking a simple example of nonlinear spacecraft control.

• Journal of the Korean Mathematical Society
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• v.34 no.4
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• pp.973-1008
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• 1997

We reconsider the problem of calssifying all classical orthogonal polynomial sequences which are solutions to a second-order differential equation of the form $$ \ell_2(x)y"(x) + \ell_1(x)y'(x) = \lambda_n y(x). $$ We first obtain new (algebraic) necessary and sufficient conditions on the coefficients $\ell_1(x)$ and $\ell_2(x)$ for the above differential equation to have orthogonal polynomial solutions. Using this result, we then obtain a complete classification of all classical orthogonal polynomials : up to a real linear change of variable, there are the six distinct orthogonal polynomial sets of Jacobi, Bessel, Laguerre, Hermite, twisted Hermite, and twisted Jacobi.cobi.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.411-418
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• 2004

Using a level set method we develop a shape optimization method applied to energy flow problems in steady state. The boundaries are implicitly represented by the level set function obtainable from the 'Hamilton-Jacobi type' equation with the 'Up-wind scheme.' The developed method defines a Lagrangian function for the constrained optimization. It minimizes a generalized compliance, satisfying the constraint of allowable volume through the variations of implicit boundary. During the optimization, the boundary velocity to integrate the Hamilton-Jacobi equation is obtained from the optimality condition for the Lagrangian function. Compared with the established topology optimization method, the developed one has no numerical instability such as checkerboard problems and easy representation of topological shape variations.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.653-654
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• 2008

This paper presents a topological shape optimization for electromagnetic system using a level set method. The optimization is progressed by updating the implicit level set function from the Hamilton-Jacobi equation. The up-wind scheme is used for numerical implementation of the Hamilton-Jacobi equation. In order to validate the proposed optimization, the core part of a C-core actuator is optimized by three cases using different materials; (single steel), (two steels), and (steel and magnet).

• Proceedings of the KIEE Conference
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• 2008.10c
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• pp.23-25
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• 2008

This paper presents a topological shape optimization for electromagnetic system using a Level Set method. The optimization is progressed by updating the implicit Level Set function from the Hamilton-Jacobi equation. The up-wind scheme is used for numerical implementation of the Hamilton-Jacobi equation. In order to validate the proposed optimization, the core part of a C-core actuator is optimized by three cases using different materials; (single steel), (two steels), and (steel and magnet).

• Journal of the Chungcheong Mathematical Society
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• v.26 no.3
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• pp.571-576
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• 2013

In this paper, we solve the optimal investment problem when the investor gets labor income and may have a wage increase. We assume the investor has constant absolute risk aversion(CARA) utility and obtain closed form solutions.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.4 no.2
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• pp.85-97
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• 2000

A quadrature rule for the solution of Cauchy singular integral equation is constructed and investigated. This method to calculate numerically singular integrals uses classical Jacobi quadratures adopting Hunter's method. The proposed method is convergent under a reasonable assumption on the smoothness of the solution.