• 경영과학
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• 제11권3호
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• pp.1-11
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• 1994

Recent advances in linear programming solution methodology have focused on interior point methods. This powerful new class of methods achieves significant reductions in computer time for large linear programs and solves problems significantly larger than previously possible. These methods can be examined from points of Fiacco and McCormick's barrier method, Lagrangian duality, Newton's method, and others. This study presents a primal-dual log barrier algorithm of interior point methods for linear programming. The primal-dual log barrier method is currently the most efficient and successful variant of interior point methods. This paper also addresses a Cholesky factorization method of symmetric positive definite matrices arising in interior point methods. A special structure of the matrices, called supernode, is exploited to use computational techniques such as direct addressing and loop-unrolling. Two dense matrix handling techniques are also presented to handle dense columns of the original matrix A. The two techniques may minimize storage requirement for factor matrix L and a smaller number of arithmetic operations in the matrix L computation.

• 음성과학
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• 제13권1호
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• pp.117-128
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• 2006

The two-channel Generalized Sidelobe Canceller (GSC) scheme suffers from the presence of leakage signal in the reference channel. The leakage signal is caused by the dissimilar impulse responses between microphones, and different paths from speech source to microphones. Such leakage is detrimental to speech enhancement of the GSC since the desired reference signal becomes corrupted. In order to suppress the signal leakage, two matrix injection methods are proposed. In the first method, a simple gain compensation matrix is used. In the second, a projection matrix for reducing the error between the actual and the ideal primary and reference signals, is used. This paper describes the performance degradation resulting from leakage, and proposes effective methods to resolve the problem. Representative experiments were conducted to demonstrate the effectiveness of the proposed methods on recorded speech and noise in an actual automobile environment.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1090-1096
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• 2001

In this paper, new methods for efficiently solving linear acceleration equations of multibody dynamic simulation exploiting sparsity for real-time simulation are presented. The coefficient matrix of the equations tends to have a large number of zero entries according to the relative joint coordinate numbering. By adequate joint coordinate numbering, the matrix has minimum off-diagonal terms and a block pattern of non-zero entries and can be solved efficiently. The proposed methods, using sparse Cholesky method and recursive block mass matrix method, take advantages of both the special structure and the sparsity of the coefficient matrix to reduce computation time. The first method solves the η$\times$η sparse coefficient matrix for the accelerations, where η denotes the number of relative coordinates. In the second method, for vehicle dynamic simulation, simple manipulations bring the original problem of dimension η$\times$η to an equivalent problem of dimension 6$\times$6 to be solved for the accelerations of a vehicle chassis. For vehicle dynamic simulation, the proposed solution methods are proved to be more efficient than the classical approaches using reduced Lagrangian multiplier method. With the methods computation time for real-time vehicle dynamic simulation can be reduced up to 14 per cent compared to the classical approach.

• International Journal of Control, Automation, and Systems
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• 제3권2호
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• pp.159-165
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• 2005

This paper designs observers for matrix second-order linear systems on the basis of generalized eigenstructure assignment via unified parametric approach. It is shown that the problem is closely related with a type of so-called generalized matrix second-order Sylvester matrix equations. Through establishing two general parametric solutions to this type of matrix equations, two unified complete parametric methods for the proposed observer design problem are presented. Both methods give simple complete parametric expressions for the observer gain matrices. The first one mainly depends on a series of singular value decompositions, and is thus numerically simple and reliable; the second one utilizes the right factorization of the system, and allows eigenvalues of the error system to be set undetermined and sought via certain optimization procedures. A spring-mass system is utilized to show the effect of the proposed approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• 전기학회논문지
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• 제57권8호
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• pp.1434-1439
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• 2008

Numerical methods for solving the state feedback control problem of linear time invariant system are presented in this paper. The methods are based on Haar wavelet approximation. The properties of Haar wavelet are first presented. The operational matrix of integration and its inverse matrix are then utilized to reduce the state feedback control problem to the solution of algebraic matrix equations. The proposed methods reduce the computation time remarkably. Finally a numerical example is illustrated to demonstrate the validity and applicability of the proposed methods.

• 대한수학회논문집
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• 제27권1호
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• pp.207-215
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• 2012

In this paper, we provide comparison results of several types of the preconditioned Gauss-Seidel methods for solving a linear system whose coefficient matrix is a Z-matrix. Lastly, numerical results are presented to illustrate the theoretical results.

• Korean Journal of Mathematics
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• 제24권4호
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• pp.681-691
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• 2016

In this note, we consider a generalized Fibonacci sequence {$q_n$}. We give a generating matrix for {$q_n$}. With the aid of this matrix, we derive and re-prove some properties involving terms of this sequence.

• 대한화학회지
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• 제22권4호
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• pp.229-238
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• 1978

Spherical harmonic의 전개방법과 쌍극자모멘트의 행렬요소를 Mulliken의 overlap integral로 전환시키는 방법을 사용하여 쌍극자모멘트의 행렬요소를 계산하는 두가지 방법을 발전시켰다. 이 두 방법에 의하여 계산한 쌍극자모멘트행렬요소의 값은 서로 일치하였다.

• 한국콘텐츠학회논문지
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• 제8권1호
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• pp.68-74
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• 2008

데이터베이스로부터 지식을 발견하고 이를 연구기획자, 정책의사결정자들이 활용하는 움직임이 전세계적으로 활발해지고 있다. 이러한 연구분야 중 대표적인 것이 계량정보학이고 이 분야를 지원하기 위해서 주로 선진국을 중심으로 분석시스템이 개발되고 있다. 그러나 외국의 분석시스템은 실제 수요자의 요구를 충분히 반영하지 못하고 있고, 고가이면서 한글이 지원되지 않아 국내 연구기획자가 사용하기에 어려운 점이 있다. 따라서 한국과학기술정보연구원에서는 이러한 단점을 극복하기 위해서 계량정보분석시스템 KnowledgeMatrix를 개발하였다. KnowledgeMatrix는 논문 및 특허의 서지정보를 분석하여 지식을 발견하기 위한 목적으로 설계된 독립형(stand-alone) 시스템이다 KnowledgeMatrix의 주요 구성을 살펴보면 행렬 생성, 클러스터링, 시각화, 데이터 전처리로 요약된다. 본 논문에서 소개하고 있는 KnowledgeMatrix는 외국의 대표적인 정보분석시스템과 비교했을 때 다양한 기능을 제공하고 있고 특히 영문데이터 처리 이외에 한글데이터 처리가 가능하다는 장점을 갖고 있다.