• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2469-2476
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• 2000

The meshing of the domain has long been the major bottleneck in performing the finite element analysis. Research efforts which are so-called meshfree methods have recently been directed towards eliminating or at least easing the requirement for meshing of the domain. In this paper, a new meshfree method for solving nonlinear boundary value problem, based on the bubble packing technique and Delaunay triangle is proposed. The method can be efficiently implemented to the problems with singularity by using formly distributed nodes.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.99-102
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• 1999

평면 배열에서 원하는 빔패턴을 얻고자 할 때 각각의 소자들의 자체 방사특성 에 의해 다른 소자가 영향을 받게된다. 보통 이러한 영향은 빔패턴의 변화를 가져올 뿐만 아니라 소자의 성능을 저하시키게 된다. 이러한 간섭을 줄이기 위해서 배열 형태를 바꾸는 등의 구조적인 개선은 많이 시도되어 왔다 그러나 이러한 개선을 통하여 영향을 줄일 수는 있으나 보다 더 정확하게 원하는 사양의 빔을 설계하기 위해서는 최적화 기법을 통하여 이러한 영향을 보상해 주어 야 한다. 본 논문에서는 빔을 설계할 때 상호 간섭 영향을 포함시킨 빔설계 알고리듬을 소개한다. 이 알고리듬은 선형 최소자승법의 해를 기반으로 최적화를 수행하고 상호 간섭의 영향은 coupling coefficients matrix를 도입하였다. 이러한 방법으로 빔을 설계하게 되면 소자의 위치 등을 변화시키지 않으면서 원하는 사양의 빔을 설계 할 수 있게 된다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.550-552
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• 2002

플러스터링이란 주어진 데이터 집합의 패턴들을 비슷한 성실을 가지는 그룹으로 나누어 패턴 상호간의 관계를 정립하기 위한 방법론으로, 지금가지 이를 위한 많은 알고리즘들이 개발되어 왔으며, 패턴인식, 영상 처리 등의 여러 공학 분야에 널리 적용되고 있다. FCM(Fuzzy C-Means) 알고리즘은 최소자승 기준함수(least square criterion function)에 퍼지이론을 적용만 목적함수의 반복최적화(iterative optimization)에 기반을 둔 방식으로, 하드 분할에 의한 기존의 클러스터링 방법이 승자(winner take all) 형태의 방법론을 취하는데 비하여, 각 패턴이 특정 클러스터에 속하는 소속정도를 줌으로써 보다 정확한 정보를 형성하도록 도와준다. 본 논문에서는 FCM 기법을 이용한 웹로그 분석을 하고자 한다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.430-433
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• 2003

This paper presents a system identification (SI) scheme in time domain using measured acceleration data. The error function is defined as the time integral of the least square errors between the measured acceleration and the calculated acceleration by a mathematical model. Damping parameters as well as stiffness properties of a structure are considered as system parameters. The structural damping is modeled by the Rayleigh damping in SI. The regularization technique is applied to alleviate the ill-posed characteristics of inverse problems. The validity of the proposed method is demonstrated by an experimental study on a shear building model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.737-747
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• 1997

performance of the cellular CDMA overlay system is analyzed which shares the same band with existing microwave narrowband system to enhance the spectral efficiency. To suppress the interfreence from narrowband system, we used a linear predicition filter that adopts the adaptive least mean square algorithm. Alalyzing the performance in the Personal Communication Services channel, characterized as a multipath Rician fadng channels, we considered the power control to solve the near-far problem, and-off and multipath diversity. We also considered interleaving and channel coding to improve BER performance of the CDMA system.

• The Journal of the Korea institute of electronic communication sciences
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• v.4 no.3
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• pp.224-229
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• 2009

In this paper, an efficient signal interference control technique to improve the convergence speed of Adaptive transversal filter with LMS algorithm is introduced. The convergence characteristics of the proposed algorithm, whose coefficients are multiply adapted in a symbol time period by recycling the received data, are analyzed to prove theoretically the improvement of convergence speed. According as the step-size parameter ${\mu}$ is increased, the rate of convergence of the algorithm is controlled. Increasing the eigenvalue spread has the effect of controlling down the rate of convergence of the adaptive equalizer and also increasing the steady-state value of the average squared error and also demonstrate the superiority of signal interference control to the filter algorithm increasing convergence speed by (B+1) times due to the data-recycling LMS Algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.691-698
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• 2003

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-l, we may compute the updated estimate of this vector at iteration n upon the arrival of new data. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. In this paper, we propose new tap weight updated RLS algorithm in adaptive transversal filter with data-recycling buffer structure. We prove that convergence speed of learning curve of RLS algorithm with data-recycling buffer is faster than it of exiting RLS algorithm to mean square error versus iteration number. Also the resulting rate of convergence is typically an order of magnitude faster than the simple LMS algorithm. We show that the number of desired sample is portion to increase to converge the specified value from the three dimension simulation result of mean square error according to the degree of channel amplitude distortion and data-recycle buffer number. This improvement of convergence character in performance, is achieved at the B times of convergence speed of mean square error increase in data recycle buffer number with new proposed RLS algorithm.

• Journal of Korean Society of Transportation
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• v.18 no.6
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• pp.89-99
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• 2000

To cope with the limits of conventional O-D trip matrix collecting methods, several approaches have been developed. One of them is bilevel Programming method Proposed by Yang(1995), which uses Sensitivity Analysis Based(SAB) algorithm to solve Generalized Least Square(GLS) problem. However, the SAB a1gorithm has revealed two critical short-comings. The first is that when there exists a significant difference between target O-D matrix and true O-D matrix, SAB algorithm may not produce correct solution. This stems from the heavy dependance on the historical O-D information, in special when gravel Patterns are dramatically changed. The second is the assumption of iterative linear approximation to original Problem. Because of the approximation, SAB algorithm has difficulty in converging to Perfect Stackelberg game condition. So as to avoid the Problems. we need a more robust and stable solution method. The main purpose of this Paper is to show the problem of the dependency of Previous models and to Propose an alternative solution method to handle it. The Problem of O-D matrix estimation is intrinsically nonlinear and nonconvex. thus it has multiple solutions. Therefore it is necessary to require a method for searching globa1 solution. In this paper, we develop a solution algorithm combined with genetic algorithm(GA) , which is widely used as probabilistic global searching method To compare the efficiency of the algorithm, SAB algorithm suggested by Yang et al. (1992,1995) is used. From the results of numerical example, the Proposed algorithm is superior to SAB algorithm irrespective of travel patterns.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.2
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• pp.20-28
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• 1998

To accurately predict the motion of a submergible, the nonlinear structure of dynamic model should be selected and corresponding parameters should be estimated using model test. Providing the model structure, only the values of parameters are unknown and the estimation can thus be formulated as a standard least square problem. Unfortunately, the nonlinear model structure of submersibles is rarely known a prior and method of model structure determination from measurement data of model test should be developed and included as a vital part of the estimation procedure. In this study, the well-known linear least square algorithm for the analysis of model tests and a way to measure the goodness are reviewed, and the identification algorithm based on an orthogonal decomposition method of Gram-Schmidt is extended to combine structure selection and maneuvering coefficients estimation in a very simple and efficient manner. Finally, the efficiency of this algorithm is verified by using simulation and applying to the analysis of model test of a submerged body. As a result, it was verified that this combined method might be very erective in selecting the structure of dynamic model estimating the maneuvering coefficients from measurement fiat of model test.

• Bulletin of the Society of Naval Architects of Korea
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• v.27 no.2
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• pp.87-95
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• 1990

Conventional methods to estimate natural frequencies and damping ratios of structures from measured response time series obtained during impact tests are reviewed. Maximum Entropy Method and Least Square Prony Method are introduced to alleviate the inherent limitation of the conventional methods. The performance of the methods are explored through computer simulation. As an example of application, they are applied to the time series obtained from an anchor drop-and-snup test of a container ship and the result is compared to that of conventional FFT method. As a result of the computer simulation, it is found that Maximum Entropy Method is very efficient to estimate natural frequencies of structures when two neighboring natural frequencies are close enough and short data records are only available, but it is not a reliable estimator for damping ratios. And it is also found that Least Square Prony Method is efficient to estimate the natural frequencies and damping ratios of highly damped structural system, but the estimation efficiency of damping ratios is significantly deteriorated in the presence of significant additive noise.