• 제목/요약/키워드: generalized eigenvalue problem

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시변 시간지연을 갖는 이산시스템의 시변 불확실성의 안정 범위 (Stability Bounds of Time-Varying Uncertainty and Delay Time for Discrete Systems with Time-Varying Delayed State)

  • 한형석
    • 제어로봇시스템학회논문지
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    • 제18권10호
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    • pp.895-901
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    • 2012
  • The stability robustness problem of linear discrete systems with time-varying unstructured uncertainty of delayed states with time-varying delay time is considered. The proposed conditions for stability can be used for finding allowable bounds of timevarying uncertainty and delay time, which are solved by using LMI (Linear Matrix Inequality) and GEVP (Generalized Eigenvalue Problem) known as powerful computational methods. Furthermore, the conditions can imply the several previous results on the uncertainty bounds of time-invariant delayed states. Numerical examples are given to show the effectiveness of the proposed algorithms.

NUMERICAL STABILITY OF UPDATE METHOD FOR SYMMETRIC EIGENVALUE PROBLEM

  • Jang Ho-Jong;Lee Sung-Ho
    • Journal of applied mathematics & informatics
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    • 제22권1_2호
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    • pp.467-474
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    • 2006
  • We present and study the stability and convergence of a deflation-preconditioned conjugate gradient(PCG) scheme for the interior generalized eigenvalue problem $Ax = {\lambda}Bx$, where A and B are large sparse symmetric positive definite matrices. Numerical experiments are also presented to support our theoretical results.

Advances in solution of classical generalized eigenvalue problem

  • Chen, P.;Sun, S.L.;Zhao, Q.C.;Gong, Y.C.;Chen, Y.Q.;Yuan, M.W.
    • Interaction and multiscale mechanics
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    • 제1권2호
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    • pp.211-230
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    • 2008
  • Owing to the growing size of the eigenvalue problem and the growing number of eigenvalues desired, solution methods of iterative nature are becoming more popular than ever, which however suffer from low efficiency and lack of proper convergence criteria. In this paper, three efficient iterative eigenvalue algorithms are considered, i.e., subspace iteration method, iterative Ritz vector method and iterative Lanczos method based on the cell sparse fast solver and loop-unrolling. They are examined under the mode error criterion, i.e., the ratio of the out-of-balance nodal forces and the maximum elastic nodal point forces. Averagely speaking, the iterative Ritz vector method is the most efficient one among the three. Based on the mode error convergence criteria, the eigenvalue solvers are shown to be more stable than those based on eigenvalues only. Compared with ANSYS's subspace iteration and block Lanczos approaches, the subspace iteration presented here appears to be more efficient, while the Lanczos approach has roughly equal efficiency. The methods proposed are robust and efficient. Large size tests show that the improvement in terms of CPU time and storage is tremendous. Also reported is an aggressive shifting technique for the subspace iteration method, based on the mode error convergence criteria. A backward technique is introduced when the shift is not located in the right region. The efficiency of such a technique was demonstrated in the numerical tests.

SOME SPECTRAL AND SCATTERING PROPERTIES OF GENERALIZED EIGENPARAMETER DEPENDENT DISCRETE TRANSMISSION STURM-LIOUVILLE EQUATION

  • Guher Gulcehre Ozbey;Guler Basak Oznur;Yelda Aygar ;Turhan Koprubasi
    • 호남수학학술지
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    • 제45권3호
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    • pp.457-470
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    • 2023
  • In this study, we set a boundary value problem (BVP) consisting of a discrete Sturm-Liouville equation with transmission condition and boundary conditions depending on generalized eigenvalue parameter. Discussing the Jost and scattering solutions of this BVP, we present scattering function and find some properties of this function. Furthermore, we obtain resolvent operator, continuous and discrete spectrum of this problem and we give an valuable asymptotic equation to get the properties of eigenvalues. Finally, we give an example to compare our results with other studies.

A PARALLEL PRECONDITIONER FOR GENERALIZED EIGENVALUE PROBLEMS BY CG-TYPE METHOD

  • MA, SANGBACK;JANG, HO-JONG
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제5권2호
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    • pp.63-69
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    • 2001
  • In this study, we shall be concerned with computing in parallel a few of the smallest eigenvalues and their corresponding eigenvectors of the eigenvalue problem, $Ax={\lambda}Bx$, where A is symmetric, and B is symmetric positive definite. Both A and B are large and sparse. Recently iterative algorithms based on the optimization of the Rayleigh quotient have been developed, and CG scheme for the optimization of the Rayleigh quotient has been proven a very attractive and promising technique for large sparse eigenproblems for small extreme eigenvalues. As in the case of a system of linear equations, successful application of the CG scheme to eigenproblems depends also upon the preconditioning techniques. A proper choice of the preconditioner significantly improves the convergence of the CG scheme. The idea underlying the present work is a parallel computation of the Multi-Color Block SSOR preconditioning for the CG optimization of the Rayleigh quotient together with deflation techniques. Multi-Coloring is a simple technique to obatin the parallelism of order n, where n is the dimension of the matrix. Block SSOR is a symmetric preconditioner which is expected to minimize the interprocessor communication due to the blocking. We implemented the results on the CRAY-T3E with 128 nodes. The MPI(Message Passing Interface) library was adopted for the interprocessor communications. The test problems were drawn from the discretizations of partial differential equations by finite difference methods.

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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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    • 제25권2E호
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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.

다양한 해석조건을 갖는 항공기에 대한 효율적인 플러터 해석 (Efficient Flutter Analysis for Aircraft with Various Analysis Conditions)

  • 이상욱;김태욱;황인희;백승길
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2005년도 추계 학술대회논문집(수송기계편)
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    • pp.49-52
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    • 2005
  • Flutter analysis procedure can be divided into two steps such as the computation of generalized mass, stiffness, and unsteady aerodynamic matrices and the calculation of major vibration modes frequency and damping values at each flight speed by solving the complex eigenvalue problem. In aircraft flutter analyses, most of the time is spent in the process of computing the unsteady aerodynamic matrices at each Mach-reduced frequency pairs defined. In this study, the method has been presented for computation and extraction of unsteady aerodynamic matrix portions dependent only on aerodynamic model using DMAP ALTER in MSC/NASTRAN SOL 145. In addition, efficient flutter analysis method has been suggested by computing and utilizing the unsteady generalized aerodynamic matrices for each analysis condition using the unsteady aerodynamic matrix portions extracted above.

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AN ACCELERATED DEFLATION TECHNIQUE FOR LARGE SYMMETRIC GENERALIZED EIGENPROBLEMS

  • HYON, YUN-KYONG;JANG, HO-JONG
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제3권1호
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    • pp.99-106
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    • 1999
  • An accelerated optimization technique combined with a stepwise deflation procedure is presented for the efficient evaluation of a few of the smallest eigenvalues and their corresponding eigenvectors of the generalized eigenproblems. The optimization is performed on the Rayleigh quotient of the deflated matrices by the aid of a preconditioned conjugate gradient scheme with the incomplete Cholesky factorization.

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데이터 마이닝을 이용한 단기부하예측 시스템 연구 (A Study on Short-Term Load Forecasting System Using Data Mining)

  • 김도완;박진배;김정찬;주영훈
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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    • pp.588-591
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    • 2003
  • This paper presents a new short-term load forecasting system using data mining. Since the electric load has very different pattern according to the day, it definitely gives rise to the forecasting error if only one forecasting model is used. Thus, to resolve this problem, the fuzzy model-based classifier and predictor are proposed for the forecasting of the hourly electric load. The proposed classifier is the multi-input and multi-output fuzzy system of which the consequent part is composed of the Bayesian classifier. The proposed classifier attempts to categorize the input electric load into Monday, Tuesday$\sim$Friday, Saturday, and Sunday electric load, Then, we construct the Takagi-Sugeno (T-S) fuzzy model-based predictor for each class. The parameter identification problem is converted into the generalized eigenvalue problem (GEVP) by formulating the linear matrix inequalities (LMIs). Finally, to show the feasibility of the proposed method, this paper provides the short-term load forecasting example.

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최적화기법을 이용한 BAM의 설계 (Design of BAM using an Optimization approach)

  • 권철희
    • 한국지능시스템학회논문지
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    • 제10권2호
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    • pp.161-167
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    • 2000
  • 본 논문에서는 양방향 연상 기능을 효과적으로 수행할 수 있는 BAM(bidirectional associative memory)의 설계방법론을 제안한다. 먼저 BAM의 성질에 관한 이론적 고찰을 바탕으로 하여 주어진 패턴 쌍을 안정하게 그리고 높은 오차수정율(error correction ratio)을 가지고 저장할 수 있는 BAM을 찾는 문제를 제약조건이 있는 최적화 문제로 공식화한다 다음과정에서 이 최적화 문제를 GEVP(generalized eigenvalue problem)로 변환함으로써 최근에 개발된 내부점 방법(interior point method)을 통하여 해가 구해질 수 있도록 한다. 제안된 설계 방법론의 적용가능성은 예제를 통해 확인된다.

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