• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.20-26
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• 2011

In this paper, we propose an efficient algorithm for reducing the complexity of LDPC code decoding by using node monitoring (NM) and Piecewise Linear Function Approximation (NP). This NM algorithm is based on a new node-threshold method, and the message passing algorithm. Piecewise linear function approximation is used to reduce the complexity for more. This algorithm was simulated in order to verify its efficiency. Simulation results show that the complexity of our NM algorithm is reduced to about 20%, compared with thoes of well-known method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2631-2635
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• 2002

The semi-analytic sensitivity analysis using Pade approximation is presented for linear elastic structures. Although the semi-analytic method has several advantages, accuracy of the method prevents it from practical application. One of promising remedies is the use of geometric series for the matrix inversion. Though series expansion of order three has been successfully applied to the calculation of the structural sensitivity in the most range of the design perturbation, it is prone to have a slow convergence for large perturbation. To overcome this shortage, Pade approximation is introduced so that it can broaden the trust region of the perturbation without adding expansion terms. Numerical results show that the confident sensitivity can be obtained with tiny expenses of computation effort.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.1087-1095
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• 2009

In this paper, we study approximation method from scattered data to the derivatives of a function f by a radial basis function $\phi$. For a given function f, we define a nearly interpolating function and discuss its accuracy. In particular, we are interested in using smooth functions $\phi$ which are (conditionally) positive definite. We estimate accuracy of approximation for the Sobolev space while the classical radial basis function interpolation applies to the so-called native space. We observe that our approximant provides spectral convergence order, as the density of the given data is getting smaller.

• Journal of Computational Design and Engineering
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• v.3 no.2
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• pp.102-111
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• 2016

In this paper, we study the problem of computing smooth feature curves from CAD type point clouds models. The proposed method reconstructs feature curves from the intersections of developable strip pairs which approximate the regions along both sides of the features. The generation of developable surfaces is based on a linear approximation of the given point cloud through a variational shape approximation approach. A line segment sequencing algorithm is proposed for collecting feature line segments into different feature sequences as well as sequential groups of data points. A developable surface approximation procedure is employed to refine incident approximation planes of data points into developable strips. Some experimental results are included to demonstrate the performance of the proposed method.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.229-241
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• 2007

Multi-term fractional differential equations have been used to simulate fractional-order control system. It has been demonstrated the necessity of the such controllers for the more efficient control of fractional-order dynamical system. In this paper, the multi-term fractional ordinary differential equations are transferred into equivalent a system of equations. The existence and uniqueness of the new system are proved. A fractional order difference approximation is constructed by a decoupled technique and fractional-order numerical techniques. The consistence, convergence and stability of the numerical approximation are proved. Finally, some numerical results are presented to demonstrate that the numerical approximation is a computationally efficient method. The new method can be applied to solve the fractional-order control system.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.506-514
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• 2008

This paper presents an intelligent model; named as free model, approach for a closed-loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. The parameters of the free model can be obtained by simultaneous perturbation stochastic approximation (SPSA) method. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. In this paper, the feasibility of the proposed method is demonstrated in a one-machine infinite bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS. The proposed SPSA-based LQR controller is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.4
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• pp.249-253
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• 2012

This paper suggests a numerical method for valuation of American options under the Kou model (double exponential jump diffusion model). The method is based on approximation of underlying asset price using a finite-state, time-homogeneous Markov chain. We examine the effectiveness of the proposed method with simulation results, which are compared with those from the conventional numerical method, the finite difference method for PIDE (partial integro-differential equation).

• Management Science and Financial Engineering
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• v.19 no.2
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• pp.37-42
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• 2013

This paper suggests a numerical method for valuation of European and American options under the two L$\acute{e}$vy Processes, Normal Inverse Gaussian Model and the Variance Gamma model. The method is based on approximation of underlying asset price using a finite-state, time-homogeneous Markov chain. We examine the effectiveness of the proposed method with simulation results, which are compared with those from the existing numerical method, the lattice-based method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.121-127
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• 2004

This paper presents a new vertex selection scheme for shape approximation. In the proposed method, final vertex points are determined by "two-step procedure". In the first step, initial vertices are simply selected on the contour, which constitute a subset of the original contour, using conventional methods such as an iterated refinement method (IRM) or a progressive vertex selection (PVS) method In the second step, a vertex adjustment Process is incorporated to generate final vertices which are no more confined to the contour and optimal in the view of the given distortion measure. For the optimality of the final vertices, the dynamic programming (DP)-based solution for the adjustment of vertices is proposed. There are two main contributions of this work First, we show that DP can be successfully applied to vertex adjustment. Second, by using DP, the global optimality in the vertex selection can be achieved without iterative processes. Experimental results are presented to show the superiority of our method over the traditional methods.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.137-146
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• 2007

In this study we consider a CONWIP system studied in Park and Lee [1] in which the processing times at each station follow a Coxian distribution and the demands for the finished products arrive according to a compound Poisson process. The demands that are not satisfied Immediately are either backordered or lost according to the number of demands that exist at their arrival instants. For this system using the results in [1] we develop an approximation method to calculate order based performance measures such as the mean time of fulfilling a customer order and the mean number of customer orders. To test the accuracy of the approximation method, the results obtained from the approximation method are compared with those obtained by simulation. Comparisons with simulation have shown that the approximate method provides fairly good results.