• Title/Summary/Keyword: matrix eigenvalue

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Improved Minimum Variance Matched field Processing Technique for Underwater Acoustic Source Localization (수중 음원 위치 추정을 위한 개선된 최소 분산 정합장 처리 기법)

  • 양인식;김준환;김기만
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1999.11a
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    • pp.169-172
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    • 1999
  • Matched field processing technique is performed by considering complex underwater environments. Specially, tile performance of minimum variance processor is greatly degraded by eigenvalue problem. In this paper, we .propose the minimum valiance matched field processor using shaping matrix. This shaping matrix makes that the input covariance matrix is invertible and enhances the desired acoustic source component. It was proved effectively range/depth localization of the proposed method with vertical array data collected by NATO SACLANT Center north of the island of Elba off the Italian west coast.

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Eigen-sensitivity Analysis of Augmented System State Matrix (전력계통의 확대상태행렬 고유치감도 해석)

  • Shim, Kwan-Shik;Nam, Hae-Kon;Kim, Yong-Gu
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.749-753
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    • 1996
  • This paper presents a new method for first and second order eigen-sensitivity analysis of system matrix in augmented form. Eigen-sensitivity analysis provides invaluable informations in power system planning and operation. However, conventional eigen-sensitivity analysis methods, which need all the eigenvalues and eigenvectors, can not be applicable to large scale power systems due to large computer memory and computing time required. In the proposed method, all sensitivity computations for a mode are carried out using the augmented system matrix and its own eigenvalue and right & left eigenvectors. In other words sensitivity analysis for a mode does not need informations on the other eigenvalues and eigenvectors and sparsity technique can be fully utilized. Thus compuations can be done very efficiently with moderate computer memory and computing time even for large power systems. The proposed algorithm is tested for one machine infinite bus system.

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Mercer Kernel Isomap

  • Choi, Hee-Youl;Choi, Seung-Jin
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.748-750
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    • 2005
  • Isomap [1] is a manifold learning algorithm, which extends classical multidimensional scaling (MDS) by considering approximate geodesic distance instead of Euclidean distance. The approximate geodesic distance matrix can be interpreted as a kernel matrix, which implies that Isomap can be solved by a kernel eigenvalue problem. However, the geodesic distance kernel matrix is not guaranteed to be positive semidefinite. In this paper we employ a constant-adding method, which leads to the Mercer kernel-based Isomap algorithm. Numerical experimental results with noisy 'Swiss roll' data, confirm the validity and high performance of our kernel Isomap algorithm.

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A Study on the Vibration Characteristics of Nonuniform Cross Section Propeller Blade (비균일 단면 외팔보형 프로펠러 날개의 진동특성에 관한 연구)

  • Chung, In-sung;Chae, Hee-chang;Park, Tae-won;Kim, Kyoung-mo;Lee, Kee-hyung;Lee, Hwan-sung
    • Journal of the Korean Society for Precision Engineering
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    • v.11 no.1
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    • pp.97-107
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    • 1994
  • The method is presented for determining the free vibration characteristics of a rotating blade having nonuniform spanwise properties and cantilever boundary condition. The equations which govern the coupled flapwise, chordwise and torsional motion of such a blade are solved using an integrating matrix method. By expressing the equation of motion in matrix notation, utilizing the integrating matrix as an operator, and applying the boundary condition, the equations are formulated into an eigenvalue problem whose solution may be determined by conventional method. Computed results are compared with experimental data.

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Development of the Vibration Analysis Program Applying the High-Performance Numerical Analysis Library (고성능 수치해석 라이브러리를 적용한 진동해석 프로그램 개발)

  • Ko, Dou-Hyun;Boo, Seung-Hwan
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.1
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    • pp.201-209
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    • 2021
  • In order to evaluate the vibrational characteristics of huge finite element models such as ships and offshore structures, it is essential to perform eigenvalue analysis and frequency response analysis. However, these analyzes necessitate excessive equipment and computation time, which require the development of a high-performance analysis program. In particular, a considerable computational analysis time is required when calculating the inverse matrix in a linear system of equations and analyzing the eigenvalue analysis. Therefore, it can be improved by applying the latest high-performance library. In this paper, the vibration analysis program that enables fast and accurate analysis was developed by applying 'PARDISO', a parallel linear system of equation calculation library, and 'ARPACK', a high-performance eigenvalue analysis library. To verify the accuracy and efficiency of proposed method, we compare ABAQUS with proposed program using numerical examples of marine engineering.

Damage assessment in periodic structures from measured natural frequencies by a sensitivity and transfer matrix-based method

  • Zhu, Hongping;Li, Lin;Wang, Dansheng
    • Structural Engineering and Mechanics
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    • v.16 no.1
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    • pp.17-34
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    • 2003
  • This paper presents a damage assessment procedure applied to periodic spring mass systems using an eigenvalue sensitivity-based method. The damage is directly related to the stiffness reduction of the damage element. The natural frequencies of periodic structures with one single disorder are found by adopting the transfer matrix approach, consequently, the first order approximation of the natural frequencies with respect to the disordered stiffness in different elements is used to form the sensitivity matrix. The analysis shows that the sensitivity of natural frequencies to damage in different locations depends only on the mode number and the location of damage. The stiffness changes due to damage can be identified by solving a set of underdetermined equations based on the sensitivity matrix. The issues associated with many possible damage locations in large structural systems are addressed, and a means of improving the computational efficiency of damage detection while maintaining the accuracy for large periodic structures with limited available measured natural frequencies, is also introduced in this paper. The incomplete measurements and the effect of random error in terms of measurement noise in the natural frequencies are considered. Numerical results of a periodic spring-mass system of 20 degrees of freedom illustrate that the proposed method is simple and robust in locating single or multiple damages in a large periodic structure with a high computational efficiency.

On triply coupled vibration of eccentrically loaded thin-walled beam using dynamic stiffness matrix method

  • Ghandi, Elham;Shiri, Babak
    • Structural Engineering and Mechanics
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    • v.62 no.6
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    • pp.759-769
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    • 2017
  • The effect of central axial load on natural frequencies of various thin-walled beams, are investigated by some researchers using different methods such as finite element, transfer matrix and dynamic stiffness matrix methods. However, there are situations that the load will be off centre. This type of loading is called eccentric load. The effect of the eccentricity of axial load on the natural frequencies of asymmetric thin-walled beams is a subject that has not been investigated so far. In this paper, the mentioned effect is studied using exact dynamic stiffness matrix method. Flexure and torsion of the aforesaid thin-walled beam is based on the Bernoulli-Euler and Vlasov theories, respectively. Therefore, the intended thin-walled beam has flexural rigidity, saint-venant torsional rigidity and warping rigidity. In this paper, the Hamilton‟s principle is used for deriving governing partial differential equations of motion and force boundary conditions. Throughout the process, the uniform distribution of mass in the member is accounted for exactly and thus necessitates the solution of a transcendental eigenvalue problem. This is accomplished using the Wittrick-Williams algorithm. Finally, in order to verify the accuracy of the presented theory, the numerical solutions are given and compared with the results that are available in the literature and finite element solutions using ABAQUS software.

Biased-Recovering Algorithm to Solve a Highly Correlated Data System (상관관계가 강한 독립변수들을 포함한 데이터 시스템 분석을 위한 편차 - 복구 알고리듬)

  • 이미영
    • Journal of the Korean Operations Research and Management Science Society
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    • v.28 no.3
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    • pp.61-66
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    • 2003
  • In many multiple regression analyses, the “multi-collinearity” problem arises since some independent variables are highly correlated with each other. Practically, the Ridge regression method is often adopted to deal with the problems resulting from multi-collinearity. We propose a better alternative method using iteration to obtain an exact least squares estimator. We prove the solvability of the proposed algorithm mathematically and then compare our method with the traditional one.

MULTIPLE SOLUTIONS FOR A CLASS OF THE SYSTEMS OF THE CRITICAL GROWTH SUSPENSION BRIDGE EQUATIONS

  • Jung, Tacksun;Choi, Q-Heung
    • Korean Journal of Mathematics
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    • v.16 no.3
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    • pp.389-402
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    • 2008
  • We show the existence of at least two solutions for a class of systems of the critical growth nonlinear suspension bridge equations with Dirichlet boundary condition and periodic condition. We first show that the system has a positive solution under suitable conditions, and next show that the system has another solution under the same conditions by the linking arguments.

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A Recursive Data Least Square Algorithm and Its Channel Equalization Application

  • Lim, Jun-Seok;Kim, Jae-Soo
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.2E
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    • pp.43-48
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    • 2006
  • Abstract-Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem, in which the error is assumed to lie in the data matrix only. Simulations demonstrate that DLS outperforms ordinary least square for certain types of deconvolution problems.