• 제목/요약/키워드: matrix domain

검색결과 571건 처리시간 0.023초

동특성 추정을 이용한 구조물의 손상도 추정 (Damage Estimation of Structures Incorporating Structural Identification)

  • Yun, Chung-Bang;Lee, Hyeong-Jin;Kim, Doo-Ki
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1995년도 봄 학술발표회 논문집
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    • pp.136-143
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    • 1995
  • The problem of the structural identification becomes important, particularly with relation to the rapid increase of the number of the damaged or deteriorated structures, such as highway bridges, buildings, and industrial facilities. This paper summarizes the recent studies related to those problems by the present authors. The system identfication methods are generally classified as the time domain and the frequency domain methods. As time doamin methods, the sequential algorithms such as the extended Kalman filter and the sequential prediction error method are studied. Several techniques for improving the convergences are incorporated. As frequency domain methods, a new frequency response function estimator is introduced. For damage estimation of existing structures, the modal perturbation and the sensitivity matrix methods are studied. From the example analysis, it has been found that the combined utilization of the measurement data for the static response and the dynamic (modal) properties are very effictive for the damage estimation.

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부구조법에 의한 영역 분할 및 강소성 유한요소해석의 병렬 계산 (Domain Decomposition using Substructuring Method and Parallel Computation of the Rigid-Plastic Finite Element Analysis)

  • 박근;양동열
    • 소성∙가공
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    • 제7권5호
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    • pp.474-480
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    • 1998
  • In the present study a domain decomposition scheme using the substructuring method is developed for the computational efficiency of the finite element analysis of metal forming processes. in order to avoid calculation of an inverse matrix during the substructuring procedure, the modified Cholesky decomposition method is implemented. As obtaining the data independence by the substructuring method the program is easily paralleized using the Parallel Virtual machine(PVM) library on a work-station cluster connected on networks. A numerical example for a simple upsetting is calculated and the speed-up ratio with respect to various number of subdomains and number of processors. The efficiency of the parallel computation is discussed by comparing the results.

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ON THE DOMAIN OF NULL-CONTROLLABILITY OF A LINEAR PERIODIC SYSTEM

  • Yoon, Byung-Ho
    • 대한수학회보
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    • 제22권2호
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    • pp.95-98
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    • 1985
  • In [1], E.B. Lee and L. Markus described a sufficient condition for which the domain of null-controllability of a linear autonomous system is all of R$^{n}$ . The purpose of this note is to extend the result to a certain linear nonautonomous system. Thus we consider a linear control system dx/dt = A(t)x+B(t)u in the Eculidean n-space R$^{n}$ where A(t) and B(t) are n*n and n*m matrices, respectively, which are continuous on 0.leq.t<.inf. and A(t) is a periodic matrix of period .omega.. Admissible controls are bounded measurable functions defined on some finite subintervals of [0, .inf.) having values in a certain convex set .ohm. in R$^{m}$ with the origin in its interior. And we present a sufficient condition for which the domain of null-controllability is all of R$^{n}$ .

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Language Model Adaptation Based on Topic Probability of Latent Dirichlet Allocation

  • Jeon, Hyung-Bae;Lee, Soo-Young
    • ETRI Journal
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    • 제38권3호
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    • pp.487-493
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    • 2016
  • Two new methods are proposed for an unsupervised adaptation of a language model (LM) with a single sentence for automatic transcription tasks. At the training phase, training documents are clustered by a method known as Latent Dirichlet allocation (LDA), and then a domain-specific LM is trained for each cluster. At the test phase, an adapted LM is presented as a linear mixture of the now trained domain-specific LMs. Unlike previous adaptation methods, the proposed methods fully utilize a trained LDA model for the estimation of weight values, which are then to be assigned to the now trained domain-specific LMs; therefore, the clustering and weight-estimation algorithms of the trained LDA model are reliable. For the continuous speech recognition benchmark tests, the proposed methods outperform other unsupervised LM adaptation methods based on latent semantic analysis, non-negative matrix factorization, and LDA with n-gram counting.

Partial Pole Assignment via Constant Gain Feedback in Two Classes of Frequency-domain Models

  • Wang, Guo-Sheng;Yang, Guo-Zhen;Duan, Guang-Ren
    • International Journal of Control, Automation, and Systems
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    • 제5권2호
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    • pp.111-116
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    • 2007
  • The design problem of partial pole assignment (PPA) in two classes of frequency-domain MIMO models by constant gain feedback is investigated in this paper. Its aim is to design a constant gain feedback which changes only a subset of the open-loop eigenvalues, while the rest of them are kept unchanged in the closed-loop system. A near general parametric expression for the feedback gain matrix in term of a set of design parameter vectors and the set of the closed-loop poles, and a simple parametric approach for solving the proposed problem are presented. The set of poles do not need to be previously prescribed, and can be set undetermined and treated together with the set of parametric vectors as degrees of design freedom provided by the approach. An illustrative example shows that the proposed parametric method is simple and effective.

An Effective Encryption Algorithm for 3D Printing Model Based on Discrete Cosine Transform

  • Pham, Ngoc-Giao;Moon, Kwnag-Seok;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • 한국멀티미디어학회논문지
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    • 제21권1호
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    • pp.61-68
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    • 2018
  • In this paper, we present an effective encryption algorithm for 3D printing models in the frequency domain of discrete cosine transform to prevent illegal copying, access in the secured storage and transmission. Facet data of 3D printing model is extracted to construct a three by three matrix that is then transformed to the frequency domain of discrete cosine transform. The proposed algorithm is based on encrypting the DC coefficients of matrixes of facets in the frequency domain of discrete cosine transform in order to generate the encrypted 3D printing model. Experimental results verified that the proposed algorithm is very effective for 3D printing models. The entire 3D printing model is altered after the encryption process. The proposed algorithm is provide a better method and more security than previous methods.

On the Modeling of Dynamic Systems

  • Suk, Jinyoung;Kim, Youdan
    • International Journal of Aeronautical and Space Sciences
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    • 제2권1호
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    • pp.78-92
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    • 2001
  • In this paper, several dynamic systems are modeled using the time domain finite element method. Galerkins' Weak Principle is used to model the general second-order mechanical system, and is applied to a simple pendulum dynamics. Problems caused by approximating the final momentum are also investigated. Extending the research, some dynamic analysis methods are suggested for the hybrid coordinate systems that have both slew and flexible modes. The proposed methods are based on both Extended Hamilton's Principle and Galerkin's Weak Principle. The matrix wave equation is propagated in space domain, satisfying the geometric/natural boundary conditions. As a result, the flexible motion can be obtained compatible with the applied control input. Numerical example is shown to demonstrate the effectiveness of the proposed modeling methods for the hybrid coordinate systems.

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3차원 다영역 공간의 소음해석을 위한 파워흐름경계요소법 개발 (Development of Power Flow Boundary Element Method for 3-dimensional Multi-domain Noise Analysis)

  • 김종도;홍석윤;송지훈
    • 한국소음진동공학회논문집
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    • 제21권10호
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    • pp.967-974
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    • 2011
  • The direct and indirect PFBEM(power flow boundary element method) for the treatment of the 3 dimensional multi-domain problems are proposed to predict the acoustic energy density in medium to high frequency ranges. In the proposed method, the equation is derived in a matrix form by considering coupled relationships of the power flow at the interface of given domains. The proposed method can successfully obtain the analytical solutions for the problems of coupled cubes and the small-scale reverberant chamber. Then the experiment is carried out to obtain STL(sound transmission loss) by using small-scale reverberant chamber and the results are compared with analysis results.

파워 스펙트럼 해석을 이용한 기준 모델 적응제어 시스템의 파라미터 수렴조건 (Conditions for Parameter Convergence of Model Reference Adaptive Control System using Power Spectrum Analysis)

  • Kim, Sung-Duck
    • 대한전기학회논문지
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    • 제38권7호
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    • pp.557-568
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    • 1989
  • Using Power Spectrum Analysis, conditions of parameter convergence for a Model Reference Adaptive Control (MRAC) system are described. The general Persistent Excitation (PE) condition given in time domain can be transformed to the positiveness of auto-correlation matrix which is represented in frequency domain by the spectra of reference input signal. For an MRAC system designed with relative degree one, the existence and the uniqueness of parameter nominal values due to the variation of input spectra can be analyzed by the PE condition in frequency domain. If the input signal has 2n spectra or more, it can be shown that the nominal values exist independent of adaptive gain, input amplitudes, and magnitudes or numbers of their spectra.

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지능적 전략계획시스템 설계를 위한 지식기초 의사결정지원체제와 인공신경망과의 결합 (Synergism of Knowledge-Based Decision Support Systems and Neural Networks to Design an Intelligent Strategic Planning System)

  • 이건창
    • Asia pacific journal of information systems
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    • 제2권1호
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    • pp.35-56
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    • 1992
  • This paper proposes a synergism of neural networks (NN) and knowledge-based decision support system (KBDSS) to effectively design an intelligent strategic planning system. Since conventional KBDSS becomes inoperative partially or totally when problem deviates slightly from the expected problem-domain, a new DSS concept is needed for designing an effective strategic planning system, where strategic planning environment is usually turbulent and consistently changing. In line with this idea, this paper developes a NN-based DSS, named ConDSS, incorporating the generalization property of NN into its knowledge base. The proposed ConDSS was extensively operated in an experimentally designed environment with three models: BCG matrix, Growth/Gain matrix, and GE matrix. The results proved very promising when encountered with unforeseen situations in comparisons with conventional KBDSS.

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