• 제목/요약/키워드: eigenvalue and eigenvector

검색결과 127건 처리시간 0.027초

Eigenstructure Assignment for Linear Systems with Probabilistic Uncertainties

  • Seo, Young-Bong;Park, Jae-Weon;Lee, Dal-Ho
    • Journal of Mechanical Science and Technology
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    • 제18권6호
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    • pp.933-945
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    • 2004
  • In this paper, S (stochastic)-eigenvalue concept and its S-eigenvector for linear continuous-time systems with probabilistic uncertainties is proposed. The proposed concept is concerned with the perturbation of eigenvalues due to the probabilistic variable parameters in the dynamic model of a plant. S-eigenstructure assignment scheme via the Sylvester equation approach based on the S-eigenvalue concept is also proposed. The proposed design schemes are illustrated by numerical examples, and applied to the longitudinal dynamics of open-loop-unstable aircraft with possible uncertainties in aerodynamic and thrust effects as well as separate dynamic pressure. These results explicitly characterize how S-eigenvalues in the complex plane may impose stability on S-eigenstructure assignment.

유사등방성과 이방성 이종재료 내의 V-노치 균열에 대한 응력특이성에 관한 연구 (A Study on Stress Singularities for V-notched Cracks in Pseudo-isotropic and Anisotropic Dissimilar Materials)

  • 조상봉;김진광
    • 한국정밀공학회지
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    • 제16권10호
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    • pp.152-163
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    • 1999
  • The problem of eigenvalue and eigenvector for v-notched cracks in pseudo-isotropic and anisotropic dissimilar materials was obtained to discuss stress singularities from traction free boundary and perfect bonded interface conditions assuming like the form of complex stress function for v-notched cracks in an isotropic material. Eigenvalues were solved by a commercial numerical program, MATHEMATICA. The relation between wedged angle and material property for eigenvalue, ${\lambda}$ indicating stress singularities of v-notched cracks in pseudo-isotropic and anisotropic dissimilar materials was examined.

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화자식별을 위한 전역 공분산에 기반한 주성분분석 (Global Covariance based Principal Component Analysis for Speaker Identification)

  • 서창우;임영환
    • 말소리와 음성과학
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    • 제1권1호
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    • pp.69-73
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    • 2009
  • This paper proposes an efficient global covariance-based principal component analysis (GCPCA) for speaker identification. Principal component analysis (PCA) is a feature extraction method which reduces the dimension of the feature vectors and the correlation among the feature vectors by projecting the original feature space into a small subspace through a transformation. However, it requires a larger amount of training data when performing PCA to find the eigenvalue and eigenvector matrix using the full covariance matrix by each speaker. The proposed method first calculates the global covariance matrix using training data of all speakers. It then finds the eigenvalue matrix and the corresponding eigenvector matrix from the global covariance matrix. Compared to conventional PCA and Gaussian mixture model (GMM) methods, the proposed method shows better performance while requiring less storage space and complexity in speaker identification.

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A Novel Eigenstructure Assignment for Linear Systems with Probabilistic Uncertainties

  • Seo, Y.B.;Choi, J.W.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.7-12
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    • 2003
  • In this paper, S(stochastic)-eigenvalue concept and its S-eigenvector for linear continuous-time systems with probabilistic uncertainties are proposed. The proposed concept is concerned with the perturbation of eigenvalues due to the probabilistic variable parameters in the dynamic model of a plant. S-eigenstructure assignment scheme via the Sylvester equation approach based on the S-eigenvalue concept is also proposed. The proposed design scheme is applied to the longitudinal dynamics of open-loop-unstable aircraft with possible uncertainties in aerodynamic and thrust effects as well as separate dynamic pressure.

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EXPLICIT MINIMUM POLYNOMIAL, EIGENVECTOR AND INVERSE FORMULA OF DOUBLY LESLIE MATRIX

  • WANICHARPICHAT, WIWAT
    • Journal of applied mathematics & informatics
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    • 제33권3_4호
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    • pp.247-260
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    • 2015
  • The special form of Schur complement is extended to have a Schur's formula to obtains the explicit formula of determinant, inverse, and eigenvector formula of the doubly Leslie matrix which is the generalized forms of the Leslie matrix. It is also a generalized form of the doubly companion matrix, and the companion matrix, respectively. The doubly Leslie matrix is a nonderogatory matrix.

정준형 상관 분석을 이용한 적응 시간 지연 추정에 관한 연구 (An Adaptive Time Delay Estimation Method Based on Canonical Correlation Analysis)

  • 임준석;홍우영
    • 한국음향학회지
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    • 제32권6호
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    • pp.548-555
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    • 2013
  • 음원 위치 추정은 여러 방면에서 쓰임이 있는 응용 기술이다. 음원의 위치를 추정하기 위한 기본 기법 중에는 시간 지연 추정 기법이 있다. 이 기법에선 음원의 위치를 추정하기 위해서 두 개 또는 그 이상의 수신기에 들어오는 신호간의 상대적 시간 지연을 알아내야 한다. 시간 지연 추정 기법에는 GCC (Generalized Cross-Correlation) 대표적이지만, 최소 고유치에 대응하는 고유 벡터를 이용하는 방법도 많이 쓰인다. 이 방법은 최소 고유치에 해당하는 고유벡터를 이용한다. 최소 고유치에 대응하는 고유 벡터를 이용하는 방법은 낮은 신호 대 잡음비 환경에서나 상관도가 있는 잡음환경에서, 최소 고유치에 해당하는 고유 벡터를 추정하는데 어려움이 있어서, 성능이 떨어진다. 본 논문에서는 정준형 상관 분석 (CCA)를 이용한 새 기법을 제안한다. 이 방법은 일반 고유치 분해 중에서 최대 고유치에 대응하는 고유벡터를 사용한다. 따라서 추정에 사용하는 고유벡터는 시간 지연 추정에 필요한 정보가 충분히 들어있다. 본 논문에서는 여러 서로 다른 신호 대 잡음비 환경 하에서 상관도가 없는 경우와 상관도가 있는 경우의 잡음 에 대해 비교 모의실험을 하였고, 이 비교 실험을 통하여 얻는 데이터를 통해서 제안한 CCA 기반 알고리즘이 기존 최소 고유치에 해당하는 고유벡터를 사용하는 시간 지연 추정법의 성능보다 더 우수하다는 것을 보인다.

General Linearly Constrained Narrowband Adaptive Arrays in the Eigenvector Space

  • Chang, Byong Kun
    • Journal of information and communication convergence engineering
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    • 제15권3호
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    • pp.137-142
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    • 2017
  • A general linearly constrained narrowband adaptive array is examined in the eigenvector space. The optimum weight vector in the eigenvector space is shown to have the same performance as in the standard coordinate system, except that the input signal correlation matrix and look direction steering vector are replaced with the eigenvalue matrix and transformed steering vector. It is observed that the variation in gain factor results in the variation in the distance between the constraint plane and the origin in the translated weight vector space such that the increase in gain factor decreased the distance from the constraint plane to the origin, thus affecting the nulling performance. Simulation results showed that the general linearly constrained adaptive array performed better at an optimal gain factor compared with the conventional linearly constrained adaptive array in a coherent signal environment and the former showed similar performance as the latter in a noncoherent signal environment.

Derivation of formulas for perturbation analysis with modes of close eigenvalues

  • Liu, X.L.
    • Structural Engineering and Mechanics
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    • 제10권5호
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    • pp.427-440
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    • 2000
  • The formulas for the perturbation analysis with modes of close eigenvalues are derived in this paper. Emphasis is made on the consistency of the straightforward perturbation process, given the complete terms of perturbations in the zeroth-order, which is a form of Rayleigh quotient, and in the higher-orders. By dividing the perturbation of eigenvector into two parts, the first-order perturbation with respect to the modes of close eigenvalues is moved into the zeroth-order perturbation. The normality condition is employed to compute the higher-order perturbations of eigenvector. The algorithm can be condensed to a single mode with a distinct eigenvalue, and this can accelerate the convergence of the perturbation analysis. The example confirms that the perturbation approximation obtained from the suggested procedure is in a good accuracy on the eigenvalues, eigenvectors, and normality.

중복근을 갖는 감쇠 시스템의 고유진동수와 모드의 민감도 (Natural Frequency and Mode Shape Sensitivities of Damped Systems with Multiple Natural Frequencies)

  • 최강민;이종헌;이인원
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2001년도 가을 학술발표회 논문집
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    • pp.515-522
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    • 2001
  • A simplified method is presented for the computation of eigenvalue and eigenvector derivatives associated with repeated eigenvalues. In the proposed method, adjacent eigenvectors and orthonormal conditions are used to compose an algebraic equation whose order is (n+m)x(n+m), where n is the number of coordinates and m is the number of multiplicity of the repeated eigenvalue. One algebraic equation developed can be computed eigenvalue and eigenvector derivatives simultaneously. Since the coefficient matrix of the proposed equation is symmetric and based on N-space, this method is very efficient compared to previous methods. Moreover the numerical stability of the method is guaranteed because the coefficient matrix of the proposed equation is non-singular, This method can be consistently applied to both structural systems with structural design parameters and mechanical systems with lumped design parameters. To verify the effectiveness of the proposed method, the finite element model of the cantilever beam and a 5-DOF mechanical system in the case of a non-proportionally damped system are considered as numerical examples. The design parameter of the cantilever beam is its width, and that of the 5-DOF mechanical system is a spring.

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상반일 등고선 적분법(RWCIM)을 이용한 이방성 이종재료 내의 V-노치 균열에 대한 고유벡터 해석 (A study on the eigenvector analyses for V-notched cracks in Anisotropic Dissimilar Materials by the Reciprocal Work Contour Integral Method)

  • 노홍래;김진광;조상봉
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2000년도 춘계학술대회논문집A
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    • pp.115-120
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    • 2000
  • This paper examines that it is possible to apply RWCIM for determining eigenvector coefficients associated with eigenvalues for V-notched cracks in anisotropic dissimilar materials using the complex stress function. To verify the RWCIM algorithm, two tests will be shown. First it is performed to ascertain whether predicted coefficients associated with eigenvectors is obtained exactly. Second, it makes an examination of the state of stress for FEM and RWCIM according to a number of eigenvectors at a location far away from the V-notched crack tip.

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