• 제목/요약/키워드: orthogonal decomposition

검색결과 218건 처리시간 0.022초

선형 격자 형성 방정식을 이용한 직교 격자 형성에 관한 연구 (Orthogonal Grid Generation Using Linear Grid Generating Equations)

  • 이상욱;권장혁;권오준
    • 한국전산유체공학회지
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    • 제5권1호
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    • pp.14-21
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    • 2000
  • A method of two and three dimensional orthogonal grid generation with control of spacing by using the covariant Laplace equation is presented. An important feature of the methodology is its ability to control effectively the grid spacing especially near the boundaries still maintaining good orthogonality in whole field. The method is based on the concept of decomposition of the global transformation into consecutive transformation of an approximate conformal mapping and an auxiliary orthogonal mapping to have linear and uncoupled equations. Control of cell spacing is based on the concept of reference arc length, and orthogonal correction is peformed in the auxiliary domain. It is concluded that the methodology can successfully generate well controlled orthogonal grids around bodies of 2 and 3 dimensional configurations.

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Modal parameter identification with compressed samples by sparse decomposition using the free vibration function as dictionary

  • Kang, Jie;Duan, Zhongdong
    • Smart Structures and Systems
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    • 제25권2호
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    • pp.123-133
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    • 2020
  • Compressive sensing (CS) is a newly developed data acquisition and processing technique that takes advantage of the sparse structure in signals. Normally signals in their primitive space or format are reconstructed from their compressed measurements for further treatments, such as modal analysis for vibration data. This approach causes problems such as leakage, loss of fidelity, etc., and the computation of reconstruction itself is costly as well. Therefore, it is appealing to directly work on the compressed data without prior reconstruction of the original data. In this paper, a direct approach for modal analysis of damped systems is proposed by decomposing the compressed measurements with an appropriate dictionary. The damped free vibration function is adopted to form atoms in the dictionary for the following sparse decomposition. Compared with the normally used Fourier bases, the damped free vibration function spans a space with both the frequency and damping as the control variables. In order to efficiently search the enormous two-dimension dictionary with frequency and damping as variables, a two-step strategy is implemented combined with the Orthogonal Matching Pursuit (OMP) to determine the optimal atom in the dictionary, which greatly reduces the computation of the sparse decomposition. The performance of the proposed method is demonstrated by a numerical and an experimental example, and advantages of the method are revealed by comparison with another such kind method using POD technique.

AN EXISTENCE OF LINEAR SYSTEMS WITH GIVEN TRANSFER FUNCTION

  • Yang, Meehyea
    • 대한수학회보
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    • 제30권1호
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    • pp.99-107
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    • 1993
  • A vector space K with scalar product <.,.> is called a Krein space if it can be decomposed as a northogonal sum of a Hilbert space and an anti-space of a Hilbert space. The space K induces a Hilbert space $K_{J}$ in the inner product <.,.> $K_{J}$=<.,.>K, where $J^{2}$=I. the eigenspaces of J are denoted by $K^{+}$$_{J}$, which is a Hilbert space and $K^{-}$$_{J}$, which is an anti-space of a Hilbert space. Then the Krein space K is the orthogonal sum of $K^{+}$$_{J}$ and $K^{-}$$_{J}$. Such a decomposition of K is called a fundamental decomposition. In general, fundamental decompositions are not unique. The norm of the Hilbert space depends on the choice of a fundamental decomposion, but such norms are equivalent. The topology generated by these norms is called the strong or Mackey topology of K. It is used to define all topological notions on the Krein space K with respect to this topology. The Pontryagin index of a Krein space is the dimension of the antispace of a Hilbert space in any such decomposition. the dimension does not depend on the choice of orthogonal decomposition. A Krein space is called a Pontryagin space if it has finite Pontryagin index.dex.yagin index.dex.

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적합직교분해 기법에서의 효율적인 스냅샷 선정을 위한 고유값 분석 (ANALYSIS OF EIGEN VALUES FOR EFFECTIVE CHOICE OF SNAPSHOT DATA IN PROPER ORTHOGONAL DECOMPOSITION)

  • 강형민;전상욱;이관중
    • 한국전산유체공학회지
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    • 제22권1호
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    • pp.59-66
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    • 2017
  • The guideline of selecting the number of snapshot dataset, $N_s$ in proper orthogonal decomposition(POD) was presented via the analysis of Eigen values based on the singular value decomposition(SVD). In POD, snapshot datasets from the solutions of Euler or Navier-Stokes equations are utilized to SVD and a reduced order model(ROM) is constructed as the combination of Eigen vectors. The ROM is subsequently applied to reconstruct the flowfield data with new set of flow conditions, thereby enhancing the computational efficiency. The overall computational efficiency and accuracy of POD is dependent on the number of snapshot dataset; however, there is no reliable guideline of determining $N_s$. In order to resolve this problem, the order of maximum to minimum Eigen value ratio, O(R) from SVD was analyzed and presented for the decision of $N_s$; in case of steady flow, $N_s$ should be determined to make O(R) be $10^9$. For unsteady flow, $N_s$ should be increased to make O(R) be $10^{11\sim12}$. This strategy of selecting the snapshot dataset was applied to two dimensional NACA0012 airfoil and vortex flow problems including steady and unsteady cases and the numerical accuracies according to $N_s$ and O(R) were discussed.

다중 사용자 OFDM 시스템의 최적 부채널 및 비트 할당: Dual-Decomposition 방법 (The Optimal Subchannel and Bit Allocation for Multiuser OFDM System: A Dual-Decomposition Approach)

  • 박태형;임성빈;서만중
    • 한국통신학회논문지
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    • 제34권1C호
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    • pp.90-97
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    • 2009
  • OFDM (Orthogonal Frequency Division Multiplexing) 전송방식의 장점은 높은 주파수 효율, RF간섭에 대한 강인성, 낮은 다중 경로 왜곡 등을 들 수 있다. 다중 사용자 OFDM의 채널용량을 확대하기 위해서는 사용자간의 부채널과 비트 할당의 효율적인 알고리즘을 개발하여야 한다. 본 연구에서는 다중 사용자의 전송요구량을 만족하는 최적 부채널 및 비트 할당 문제를 0-1 정수계획법 모형으로 형성하고, 원래 문제의 선형계획법 완화 (linear programming relaxation)문제를 dual-decomposition과 subgradient 알고리즘을 사용하여 해를 구하는 효과적인 알고리즘을 제시한다. 또한 dual-decomposition으로 구한 목적함수값은 원래 문제의 선형계획법 완화문제의 최적목적함수 간과 동일함을 증명하였다 모의실험을 통하여 다수의 문제에 대하여 원래 문제의 최적 목적항수값에 대한 dual-decomposition으로 구한 하한의 성능을 제시하였다. MQAM (M-ary Quadrature Amplitude Modulation)을 사용하고 3개의 독립적인 Rayleigh 다중 경로로 구성된 주파수 선택적 채널을 가정한 경우 MATLAB을 사용한 모의실험에서 0-1 정수계획 법으로 구한 최적해의 성능을 실험하였다.

선형 격자 형성 방정식을 이용한 직교 격자 형성에 관한 연구 (Orthogonal Grid Generation Using Linear Grid Generating Equations)

  • 이상욱;권장혁;권오준
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2000년도 춘계 학술대회논문집
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    • pp.99-106
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    • 2000
  • A method of two and three dimensional orthogonal grid generation with control of spacing by using the covariant Laplace equation is Presented. An important feature of the methodology is its ability to control effectively the grid spacing especially near the boundaries still maintaining good orthogonality in whole field. The method is based on the concept of decomposition of the global transformation into consecutive transformation of an approximate conformal mapping and au auxiliary orthogonal mapping to have linear and uncoupled equations. Control of cell spacing is based on the concept of reference arc length, and orthogonal correction is performed in the auxiliary domain. It is concluded that the methodology can successfully generate well controlled orthogonal grids around bodies of 2 and 3 dimensional configurations.

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Nonnegative Matrix Factorization with Orthogonality Constraints

  • Yoo, Ji-Ho;Choi, Seung-Jin
    • Journal of Computing Science and Engineering
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    • 제4권2호
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    • pp.97-109
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    • 2010
  • Nonnegative matrix factorization (NMF) is a popular method for multivariate analysis of nonnegative data, which is to decompose a data matrix into a product of two factor matrices with all entries restricted to be nonnegative. NMF was shown to be useful in a task of clustering (especially document clustering), but in some cases NMF produces the results inappropriate to the clustering problems. In this paper, we present an algorithm for orthogonal nonnegative matrix factorization, where an orthogonality constraint is imposed on the nonnegative decomposition of a term-document matrix. The result of orthogonal NMF can be clearly interpreted for the clustering problems, and also the performance of clustering is usually better than that of the NMF. We develop multiplicative updates directly from true gradient on Stiefel manifold, whereas existing algorithms consider additive orthogonality constraints. Experiments on several different document data sets show our orthogonal NMF algorithms perform better in a task of clustering, compared to the standard NMF and an existing orthogonal NMF.

Fundamental Frequency Estimation in Power Systems Using Complex Prony Analysis

  • Nam, Soon-Ryul;Lee, Dong-Gyu;Kang, Sang-Hee;Ahn, Seon-Ju;Choi, Joon-Ho
    • Journal of Electrical Engineering and Technology
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    • 제6권2호
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    • pp.154-160
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    • 2011
  • A new algorithm for estimating the fundamental frequency of power system signals is presented. The proposed algorithm consists of two stages: orthogonal decomposition and a complex Prony analysis. First, the input signal is decomposed into two orthogonal components using cosine and sine filters, and a variable window is adapted to enhance the performance of eliminating harmonics. Then a complex Prony analysis that is proposed in this paper is used to estimate the fundamental frequency by approximating the cosine-filtered and sine-filtered signals simultaneously. To evaluate the performance of the algorithm, amplitude modulation and harmonic tests were performed using simulated test signals. The performance of the algorithm was also assessed for dynamic conditions on a single-machine power system. The Electromagnetic Transients Program was used to generate voltage signals for a load increase and single phase-to-ground faults. The performance evaluation showed that the proposed algorithm accurately estimated the fundamental frequency of power system signals in the presence of amplitude modulation and harmonics.

Structural identification based on incomplete measurements with iterative Kalman filter

  • Ding, Yong;Guo, Lina
    • Structural Engineering and Mechanics
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    • 제59권6호
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    • pp.1037-1054
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    • 2016
  • Structural parameter evaluation and external force estimation are two important parts of structural health monitoring. But the structural parameter identification with limited input information is still a challenging problem. A new simultaneous identification method in time domain is proposed in this study to identify the structural parameters and evaluate the external force. Each sampling point in the time history of external force is taken as the unknowns in force evaluation. To reduce the number of unknowns for force evaluation the time domain measurements are divided into several windows. In each time window the structural excitation is decomposed by orthogonal polynomials. The time-variant excitation can be represented approximately by the linear combination of these orthogonal bases. Structural parameters and the coefficients of decomposition are added to the state variable to be identified. The extended Kalman filter (EKF) is augmented and selected as the mathematical tool for the implementation of state variable evaluation. The proposed method is validated numerically with simulation studies of a time-invariant linear structure, a hysteretic nonlinear structure and a time-variant linear shear frame, respectively. Results from the simulation studies indicate that the proposed method is capable of identifying the dynamic load and structural parameters fairly accurately. This method could also identify the time-variant and nonlinear structural parameter even with contaminated incomplete measurement.