• Title/Summary/Keyword: Eigenvalue decomposition

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A study on the proper orthogonal decomposition of the structural dynamic system (구조진동시스템의 적합직교분해에 관한 연구)

  • Baek, Sung-Min;Cho, Maeng-Hyo
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2010.04a
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    • pp.171-174
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    • 2010
  • 적절한 근사화 과정을 통하여 구축된 축소 시스템은 전체 시스템의 거동을 적은 수의 정보를 통하여 효과적으로 표현할 수 있다. 효과적인 시스템 축소를 위하여 본 연구에서는 주파수 영역 Karhunen-Loeve (Frequency-domain Karhunen-Loeve, FDKL) 기법과 시스템 등가 확장 축소 과정(System equivalent expansion reduction process, SEREP)을 연동한 축소 기법을 제안한다. 적합직교분해(Proper orthogonal decomposition)의 한 방법인 FDKL기법을 통하여 최적모드(Optimal mode)를 구하고 이에 SEREP을 적용하여 자유도 변환 행렬을 구한다. 이때 주자유도 선정은 2단계 축소기법을 적용한다. 최종적으로 제안된 기법은 수치예제를 통하여 검증한다.

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Underwater Transient Signal Classification Using Eigen Decomposition Based on Wigner-Ville Distribution Function (위그너-빌 분포 함수 기반의 고유치 분해를 이용한 수중 천이 신호 식별)

  • Bae, Keun-Sung;Hwang, Chan-Sik;Lee, Hyeong-Uk;Lim, Tae-Gyun
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.3
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    • pp.123-128
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    • 2007
  • This Paper Presents new transient signal classification algorithms for underwater transient signals. In general. the ambient noise has small spectral deviation and energy variation. while a transient signal has large fluctuation. Hence to detect the transient signal, we use the spectral deviation and power variation. To classify the detected transient signal. the feature Parameters are obtained by using the Wigner-Ville distribution based eigenvalue decomposition. The correlation is then calculated between the feature vector of the detected signal and all the feature vectors of the reference templates frame-by-frame basis, and the detected transient signal is classified by the frame mapping rate among the class database.

Antenna array for estimation of direction of arrival utilizing modified minimum eigenvalue searching (개선된 MES 방법을 이용한 신호의 도래각(DOA) 추정을 위한 배열안테나)

  • 이현배;최승원
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.4
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    • pp.164-173
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    • 1996
  • This paper presents an alternative technique for DOA (direction-of-arrival) estimation. For generating a weight vector orthogonal to the signal subspace, a modified version of MES (minimum eigenvalue searching ) method is introduced. The performance of the proposed technique is compared to that of the conventional ED (eigen decomposition) method in terms of angle resolution for a number of snapshots during agiven observation period as well as various SNR's. In addition, the superiority of the suggested technique is shown, by analyzing the required computational load of the proposed MES and conventional ED method. A novel procedure of simplifying the MES proposed in [1] is presented on that purpose. Another advnatage of the proposed technique is that it is performed independently of the detection of the number of signal components, which makes it possible to estimate the DOA's of clusters consisting of infinite number of inseparable signal components.

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Power Spectral Estimation of Background EEG with LMS PHD (LMS PHD에 의한 배경단파 파워 스펙트럼 추정)

  • 정명진;최갑석
    • Journal of Biomedical Engineering Research
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    • v.9 no.1
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    • pp.101-108
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    • 1988
  • In this paper the power spectrum of background EEG is estimated by the LMS PHD based on least mean square. At the power spectrum estimatiom, the stocastic process of background EEG is assumed to consist of the nonharmonic sinusoid and the white noise. In the LMS PHD the model parameters are obtained by the least mean square at optimal order which is obtained from the fact that the eigenvalue's fluctuation of autocorrelation matrix of the normal back-ground EEG is smaller at some order than at other order when the power spectrum of background EEG is esitmated by PHD. The optimal order of this model is the 6-th order when the eigenvalue's fluctuation of autocorrelation matrix of background EEG is considered. The estimation results are with compared the results from the Maximum Entropy Spectral Estimation and Pisarenko Harmonic Decomposition. From the comparison results. The LMS PHD is possible to estimate the power spectrum of background EEG.

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Understanding of unsteady pressure fields on prisms based on covariance and spectral proper orthogonal decompositions

  • Hoa, Le Thai;Tamura, Yukio;Matsumoto, Masaru;Shirato, Hiromichi
    • Wind and Structures
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    • v.16 no.5
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    • pp.517-540
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    • 2013
  • This paper presents applications of proper orthogonal decomposition in both the time and frequency domains based on both cross spectral matrix and covariance matrix branches to analyze multi-variate unsteady pressure fields on prisms and to study spanwise and chordwise pressure distribution. Furthermore, modification of proper orthogonal decomposition is applied to a rectangular spanwise coherence matrix in order to investigate the spanwise correlation and coherence of the unsteady pressure fields. The unsteady pressure fields have been directly measured in wind tunnel tests on some typical prisms with slenderness ratios B/D=1, B/D=1 with a splitter plate in the wake, and B/D=5. Significance and contribution of the first covariance mode associated with the first principal coordinates as well as those of the first spectral eigenvalue and associated spectral mode are clarified by synthesis of the unsteady pressure fields and identification of intrinsic events inside the unsteady pressure fields. Spanwise coherence of the unsteady pressure fields has been mapped the first time ever for better understanding of their intrinsic characteristics.

Signal parameter estimation through hierarchical conjugate gradient least squares applied to tensor decomposition

  • Liu, Long;Wang, Ling;Xie, Jian;Wang, Yuexian;Zhang, Zhaolin
    • ETRI Journal
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    • v.42 no.6
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    • pp.922-931
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    • 2020
  • A hierarchical iterative algorithm for the canonical polyadic decomposition (CPD) of tensors is proposed by improving the traditional conjugate gradient least squares (CGLS) method. Methods based on algebraic operations are investigated with the objective of estimating the direction of arrival (DoA) and polarization parameters of signals impinging on an array with electromagnetic (EM) vector-sensors. The proposed algorithm adopts a hierarchical iterative strategy, which enables the algorithm to obtain a fast recovery for the highly collinear factor matrix. Moreover, considering the same accuracy threshold, the proposed algorithm can achieve faster convergence compared with the alternating least squares (ALS) algorithm wherein the highly collinear factor matrix is absent. The results reveal that the proposed algorithm can achieve better performance under the condition of fewer snapshots, compared with the ALS-based algorithm and the algorithm based on generalized eigenvalue decomposition (GEVD). Furthermore, with regard to an array with a small number of sensors, the observed advantage in estimating the DoA and polarization parameters of the signal is notable.

A Note on Eigenstructure of a Spatial Design Matrix In R1

  • Kim Hyoung-Moon;Tarazaga Pablo
    • Communications for Statistical Applications and Methods
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    • v.12 no.3
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    • pp.653-657
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    • 2005
  • Eigenstructure of a spatial design matrix of Matheron's variogram estimator in $R^1$ is derived. It is shown that the spatial design matrix in $R^1$ with n/2$\le$h < n has a nice spectral decomposition. The mean, variance, and covariance of this estimator are obtained using the eigenvalues of a spatial design matrix. We also found that the lower bound and the upper bound of the normalized Matheron's variogram estimator.

Speaker Localization in Reverberant Environments Using Sparse Priors on Acoustic Channels (음향 채널의 '성김' 특성을 이용한 반향환경에서의 화자 위치 탐지)

  • Cho, Ji-Won;Park, Hyung-Min
    • MALSORI
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    • no.67
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    • pp.135-147
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    • 2008
  • In this paper, we propose a method for source localization in reverberant environments based on an adaptive eigenvalue decomposition (AED) algorithm which directly estimates channel impulse responses from a speaker to microphones. Unfortunately, the AED algorithm may suffer from whitening effects on channels estimated from temporally correlated natural sounds. The proposed method which applies sparse priors to the estimated channels can avoid the temporal whitening and improve the performance of source localization in reverberant environments. Experimental results show the effectiveness of the proposed method.

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A DIRECT SOLVER FOR THE LEGENDRE TAU APPROXIMATION FOR THE TWO-DIMENSIONAL POISSON PROBLEM

  • Jun, Se-Ran;Kang, Sung-Kwon;Kwon, Yong-Hoon
    • Journal of applied mathematics & informatics
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    • v.23 no.1_2
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    • pp.25-42
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    • 2007
  • A direct solver for the Legendre tau approximation for the two-dimensional Poisson problem is proposed. Using the factorization of symmetric eigenvalue problem, the algorithm overcomes the weak points of the Schur decomposition and the conventional diagonalization techniques for the Legendre tau approximation. The convergence of the method is proved and numerical results are presented.

Buckling of rectangular plates with mixed edge supports

  • Xiang, Y.;Su, G.H.
    • Structural Engineering and Mechanics
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    • v.14 no.4
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    • pp.401-416
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    • 2002
  • This paper presents a domain decomposition method for buckling analysis of rectangular Kirchhoff plates subjected to uniaxial inplane load and with mixed edge support conditions. A plate is decomposed into two rectangular subdomains along the change of the discontinuous support conditions. The automated Ritz method is employed to derive the governing eigenvalue equation for the plate system. Compatibility conditions are imposed for transverse displacement and slope along the interface of the two subdomains by modifying the Ritz trial functions. The resulting Ritz function ensures that the transverse displacement and slope are continuous along the entire interface of the two subdomains. The validity and accuracy of the proposed method are verified with convergence and comparison studies. Buckling results are presented for several selected rectangular plates with various combination of mixed edge support conditions.