• Title/Summary/Keyword: eigen analysis

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Levy-type solution for analysis of a magneto-electro-elastic panel

  • Jia He;Xuejiao Zhang;Hong Gong;H. Elhosiny Ali;Elimam Ali
    • Steel and Composite Structures
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    • v.46 no.6
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    • pp.719-729
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    • 2023
  • This paper studies electro-magneto-mechanical bending studying of the cylindrical panels based on shear deformation theory. The cylindrical panel is constrained with two simply-supported edges at longitudinal direction and two clamped boundary conditions at circumferential direction. The governing equations are derived based on the principle of virtual work in cylindrical coordinate system. Levy-type solution of the governing equations is derived to reduce two dimensional PDEs to a 2D ODEs. The reduced ordinary differential equation is solved using the Eigen-value Eigen-vector method for the clamped-clamped boundary condition. The electro-magneto-mechanical bending results are obtained to show that every displacement, rotation and electromagnetic potentials how change with changes of initial electromagnetic potentials and mechanical loads along longitudinal and circumferential directions.

An Object Detection System using Eigen-background and Clustering (Eigen-background와 Clustering을 이용한 객체 검출 시스템)

  • Jeon, Jae-Deok;Lee, Mi-Jeong;Kim, Jong-Ho;Kim, Sang-Kyoon;Kang, Byoung-Doo
    • Journal of Korea Multimedia Society
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    • v.13 no.1
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    • pp.47-57
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    • 2010
  • The object detection is essential for identifying objects, location information, and user context-aware in the image. In this paper, we propose a robust object detection system. The System linearly transforms learning data obtained from the background images to Principal components. It organizes the Eigen-background with the selected Principal components which are able to discriminate between foreground and background. The Fuzzy-C-means (FCM) carries out clustering for images with inputs from the Eigen-background information and classifies them into objects and backgrounds. It used various patterns of backgrounds as learning data in order to implement a system applicable even to the changing environments, Our system was able to effectively detect partial movements of a human body, as well as to discriminate between objects and backgrounds removing noises and shadows without anyone frame image for fixed background.

Analysis of SAR Interference Suppression Techniques using Eigen-subspace based Filter (고유치 기반 필터를 이용한 위성 SAR 영상 간섭신호 제거 기법)

  • Lee, Bo-Yun;Kim, Bum-Seung;Song, Jung-Hwan;Lee, Woo-Kyung
    • Journal of Satellite, Information and Communications
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    • v.12 no.3
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    • pp.63-68
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    • 2017
  • SAR(Synthetic Aperture Radar) uses electromagnetic signals to acquire ground information and has been used for wide coverage reconnaissance missions regardless of weather conditions. However SAR is known to be vulnerable to interference signals by other communication devices or radar instruments and may suffer from undesirable performance degradations and image quality. In this paper, a modified Eigen-subspace based filter is proposed that can be easily applied to SAR images affected by interference signals. The method of constructing Eigen-subspace based filter is briefly described and various simulations are performed to show the performance of the interference mitigation process. The suppression filter is applied to a ALOS PALSAR raw data affected by interfering signals in order to verify its superiority over the Notch filter.

Histogram Equalized Eigen Co-occurrence Features for Color Image Classification (컬러이미지 검색을 위한 히스토그램 평활화 기반 고유 병발 특징에 관한 연구)

  • Yoon, TaeBok;Choi, YoungMee;Choo, MoonWon
    • Annual Conference of KIPS
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    • 2010.11a
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    • pp.705-708
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    • 2010
  • An eigen color co-occurrence approach is proposed that exploits the correlation between color channels to identify the degree of image similarity. This method is based on traditional co-occurrence matrix method and histogram equalization. On the purpose of feature extraction, eigen color co-occurrence matrices are computed for extracting the statistical relationships embedded in color images by applying Principal Component Analysis (PCA) on a set of color co-occurrence matrices, which are computed on the histogram equalized images. That eigen space is created with a set of orthogonal axes to gain the essential structures of color co-occurrence matrices, which is used to identify the degree of similarity to classify an input image to be tested for various purposes. In this paper RGB, Gaussian color space are compared with grayscale image in terms of PCA eigen features embedded in histogram equalized co-occurrence features. The experimental results are presented.

A Study on the Eigen Ethnic Function and Mathematical Processing Method of Human Information (인적정보의 고유기능과 계량화 방안에 관한 연구)

  • 김홍재;서윤정
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.19 no.40
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    • pp.329-339
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    • 1996
  • This study presents the eigen ethnic function and mathematical processing method of human information. Human information can be definded as the overlap area taking the superposition property composed of intuition and sensory in stimulus/response (S/R) model, In S/R model, the intuition and sensory eigen ethnic function acts on the forming of perception. Perception process by the superposition property of intuition and sensory analogy to the basic neural network model. This analogy model extends to the analysis method. As an analysis method, optimal ratio number induced to the golden section ratio. Golden section ratio drived out by diverse source and implicated to the sensory and intuitive context such as beauty, harmony, optimality etc. This numerical orders can be applied to analysing the Perception process and extended to pursue the Potential human behavior, On the basic of proposed applying method, an illustrative mathematical examples are presented.

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Free vibration analysis of concrete arch dams by quadratic ideal-coupled method

  • Rezaiee-Pajand, Mohammad;Sani, Ahmad Aftabi;Kazemiyan, Mohammad Sadegh
    • Structural Engineering and Mechanics
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    • v.65 no.1
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    • pp.69-79
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    • 2018
  • This paper is devoted to two new techniques for free vibration analysis of concrete arch dam-reservoir systems. The proposed schemes are quadratic ideal-coupled eigen-problems, which can solve the originally non-symmetric eigen-problem of the system. To find the natural frequencies and mode shapes, a new special-purpose eigen-value solution routine is developed. Moreover, the accuracy of the proposed approach is thoroughly assessed, and it is confirmed that the new scheme is very accurate under all practical conditions. It is also concluded that both decoupled and ideal-coupled strategy proposed in the previous works can be considered as special cases of the current more general procedure.

Partitioned structural eigenvalue analysis (부분 구조물 합성으로 이루어진 고유치 문제 해석)

  • Jung, Eui-Il;Na, Hye-Joong;No, Suk-Hong;Chun, Du-Hwan
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.05a
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    • pp.117-119
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    • 2005
  • For large structural eigen-analysis, the whole structure is divided into some partitioned structures and through synthesis of partitioned structural model the eigen-data of structure can be obtained. In that case, eigenvalue problem consists of semidefinite mass matrix form because of displacement constraint condition. In this work the eigenvalue problem is considered by means of several method, determinant search and null space reduction method.

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

  • Kang, H.M.;Jun, S.O.;Yee, K.
    • Journal of computational fluids engineering
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    • v.22 no.1
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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.

Convergence Decision Method Using Eigenvectors of QR Iteration (QR 반복법의 고유벡터를 이용한 수렴 판단 방법)

  • Kim, Daehyun;Lee, Jingu;Jeong, Seonghee;Lee, Jaeeun;Kim, Younglok
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.8
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    • pp.868-876
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    • 2016
  • MUSIC (multiple signal classification) algorithm is a representative algorithm estimating the angle of arrival using the eigenvalues and eigenvectors. Generally, the eigenvalues and eigenvectors are obtained through the eigen-analysis, but this analysis requires high computational complexity and late convergence time. For this reason, it is almost impossible to construct the real-time system with low-cost using this approach. Even though QR iteration is considered as the eigen-analysis approach to improve these problems, this is inappropriate to apply to the MUSIC algorithm. In this paper, we analyze the problems of conventional method based on the eigenvalues for convergence decision and propose the improved decision algorithm using the eigenvectors.

A dissipative family of eigen-based integration methods for nonlinear dynamic analysis

  • Chang, Shuenn-Yih
    • Structural Engineering and Mechanics
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    • v.75 no.5
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    • pp.541-557
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    • 2020
  • A novel family of controllable, dissipative structure-dependent integration methods is derived from an eigen-based theory, where the concept of the eigenmode can give a solid theoretical basis for the feasibility of this type of integration methods. In fact, the concepts of eigen-decomposition and modal superposition are involved in solving a multiple degree of freedom system. The total solution of a coupled equation of motion consists of each modal solution of the uncoupled equation of motion. Hence, an eigen-dependent integration method is proposed to solve each modal equation of motion and an approximate solution can be yielded via modal superposition with only the first few modes of interest for inertial problems. All the eigen-dependent integration methods combine to form a structure-dependent integration method. Some key assumptions and new techniques are combined to successfully develop this family of integration methods. In addition, this family of integration methods can be either explicitly or implicitly implemented. Except for stability property, both explicit and implicit implementations have almost the same numerical properties. An explicit implementation is more computationally efficient than for an implicit implementation since it can combine unconditional stability and explicit formulation simultaneously. As a result, an explicit implementation is preferred over an implicit implementation. This family of integration methods can have the same numerical properties as those of the WBZ-α method for linear elastic systems. Besides, its stability and accuracy performance for solving nonlinear systems is also almost the same as those of the WBZ-α method. It is evident from numerical experiments that an explicit implementation of this family of integration methods can save many computational efforts when compared to conventional implicit methods, such as the WBZ-α method.